SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC On-Demand

Computational Fluid Dynamics
Presentation
Media
Fast Fixed-Radius Nearest Neighbor Search on the GPU: Interactive Million-Particle Fluids
Rama Hoetzlein (NVIDIA)
Nearest neighbor search is the key to efficient simulation of many discrete physical models. This talk focuses on a novel, efficient fixed-radius NNS by introducing counting sort accelerated with atomic GPU operations which require only two kernel ca ...Read More
Nearest neighbor search is the key to efficient simulation of many discrete physical models. This talk focuses on a novel, efficient fixed-radius NNS by introducing counting sort accelerated with atomic GPU operations which require only two kernel calls. As a sample application, fluid simulations based on smooth particles hydrodynamics (SPH) make use of NNS to determine interacting fluid particles. The Counting-sort NNS method achieves a performance gain of 3-5x over previous Radix-sort NNS, which allows for interactive SPH fluids of 4 million particles at 4 fps on current hardware. The technique presented is generic and easily adapted to other domains, such as molecular interactions or point cloud reconstructions.   Back
 
Keywords:
Computational Fluid Dynamics, Numerical Algorithms & Libraries, Developer - Performance Optimization, Molecular Dynamics, GTC Silicon Valley 2014 - ID S4117
Streaming:
Download:
Computational Physics
Presentation
Media
Efficient Computation of Radial Distribution Function on GPUs: Algorithm Design and Optimization
Yicheng Tu (University of South Florida), Anand Kumar (University of South Florida)
The radial distribution function (RDF) is a fundamental tool in validation and analysis of particle simulation data. Computation of RDF is a very time expensive process. It may take days or even months to process moderate size data points (millions) ...Read More
The radial distribution function (RDF) is a fundamental tool in validation and analysis of particle simulation data. Computation of RDF is a very time expensive process. It may take days or even months to process moderate size data points (millions) on CPU. We present an efficient technique to compute RDF on GPUs, which takes advantage of shared memory, registers, and special instructions. Recent GPU architectures support shuffle instruction that can be used to share data between threads, via registers. We exploit these features of the new architecture to improve performance of the RDF algorithm. Further, we present benefits of using different GPU optimization techniques to improve the performance. Effect of algorithm behavior on the speedup is also presented in detail with the help of examples.   Back
 
Keywords:
Computational Physics, Big Data Analytics, Molecular Dynamics, GTC Silicon Valley 2014 - ID S4149
Streaming:
 
GPU-Accelerated Modeling of Coherent Processes in Magnetic Nano-Structures
Aleksey Demenev (Perm State University)
Multi-scale molecular dynamics of the systems of nanomagnets is investigated by numerical simulation using parallel algorithms. Fortran- code Magnetodynamics-F provides next types of research: study of the possibility of regulation time of switc ...Read More

Multi-scale molecular dynamics of the systems of nanomagnets is investigated by numerical simulation using parallel algorithms. Fortran- code Magnetodynamics-F provides next types of research: study of the possibility of regulation time of switching of the magnetic moment of the nanostructure; estimation of the role of nanocrystal geometry on super-radiation of 1-, 2- and 3-dimensional objects; study of magnetodynamics of a nanodots inductively coupled with the passive resonator; depending on the solution from initial orientation of the magnetic moment in order to find the configurations for which the super-radiance and radiative damping are maximal. The parallel programs created using application programming interfaces OpenMP and OpenACC. The estimates of speedup and efficiency of implemented algorithms in comparison with sequential algorithms have been obtained. It is shown that the use of NVIDIA Tesla accelerates simulation for study of magnetic dynamics systems which include thousands of magnetic nanoparticles.

  Back
 
Keywords:
Computational Physics, Numerical Algorithms & Libraries, Molecular Dynamics, GTC Silicon Valley 2014 - ID S4493
Download:
Developer - Performance Optimization
Presentation
Media
Resolving False Dependence on Shared Memory
Patric Zhao (NVIDIA)
Large-scale shared memory provided by GPU can hugely improve the performance of applications and the shared memory programming model has been widely used for commercial and scientific purpose.However, a plenty of barriers arise when the shared memory ...Read More
Large-scale shared memory provided by GPU can hugely improve the performance of applications and the shared memory programming model has been widely used for commercial and scientific purpose.However, a plenty of barriers arise when the shared memory is immoderately employed, which causes most of running time wasted on synchronization. Furthermore, false dependence issue occurs in some cases and it may dramatically depress the performance. In this session,we demonstrate how to identify false dependence issues. Meanwhile,we propose various strategies and solutions to deal with false dependence issue from both application algorithm and GPU kernel level. Performance analysis on NAMD, a very popular molecular dynamics program, has been done and the code example is provided. By applying our strategies, the effective occupancy is improved to 0.98 and the synchronization time is reduced by 70%, which finally brings about 30% performance increments.  Back
 
Keywords:
Developer - Performance Optimization, Molecular Dynamics, GTC Silicon Valley 2014 - ID S4279
Streaming:
Download:
General Interest
Presentation
Media
GPU Accelerated Visualization and Analysis in VMD
John Stone
State-of-the-art graphics processing units (GPUs) contain hundreds of processing units and are able to perform trillions of floating point arithmetic operations per second. ...Read More
State-of-the-art graphics processing units (GPUs) contain hundreds of processing units and are able to perform trillions of floating point arithmetic operations per second. The newly available computational power brought by GPUs is enabling a new generation of scientific and engineering applications to perform calculations on "personal supercomputers" that previously required HPC clusters or that were otherwise impractical in everyday use. This talk will present recent successes in multi-GPU acceleration in VMD, a molecular dynamics visualization and analysis application in which GPU computing techniques have provided speedups ranging from 10 to over 100 times faster than commodity CPU cores. The talk will describe key challenges and algorithmic strategies involved in achieving high computational performance on GPUs, discuss methods for effectively using multiple GPUs in low-latency calculations that drive interactive visualizations, and will also include some examples of how these performance increases ultimately enable better science.   Back
 
Keywords:
General Interest, Life & Material Science, Molecular Dynamics, Visualization, GTC Silicon Valley 2009 - ID S09053
Streaming:
Download:
HPC and Supercomputing
Presentation
Media
Attacking HIV with Petascale Molecular Dynamics Simulations on Titan and Blue Waters
James Phillips (University of Illinois)
The highly parallel molecular dynamics code NAMD was chosen in 2006 as a target application for the NSF petascale supercomputer now know as Blue Waters. NAMD was also one of the first codes to run on a GPU cluster when G80 and CUDA were introduced i ...Read More
The highly parallel molecular dynamics code NAMD was chosen in 2006 as a target application for the NSF petascale supercomputer now know as Blue Waters. NAMD was also one of the first codes to run on a GPU cluster when G80 and CUDA were introduced in 2007. When Blue Waters entered production in 2013, the first breakthrough it enabled was the complete atomic structure of the HIV capsid through calculations using NAMD, featured on the cover of Nature. How do the GPU-accelerated Cray XK7 Blue Waters and ORNL Titan machines compare to CPU-based platforms for a 64-million-atom virus simulation? Come learn the opportunities and pitfalls of taking GPU computing to the petascale and the importance of CUDA 5.5 and Kepler features in combining multicore host processors and GPUs in a legacy message-driven application.  Back
 
Keywords:
HPC and Supercomputing, Molecular Dynamics, GTC Silicon Valley 2014 - ID S4394
Streaming:
Download:
Life & Material Science
Presentation
Media
Folding@home: Petaflops on the Cheap Today; Exaflops Soon?
Vijay Pande
Learn how Folding@home has used petascale computing with GPUs to make fundamental breakthroughs in computational biology and how this technology can make an impact in your work. ...Read More

Learn how Folding@home has used petascale computing with GPUs to make fundamental breakthroughs in computational biology and how this technology can make an impact in your work.

  Back
 
Keywords:
Life & Material Science, Cloud Visualization, HPC and AI, Molecular Dynamics, GTC Silicon Valley 2010 - ID S10007
Download:
 
Computational Biophysics and Long Range Electrostatics on GPUs
Scott Le
This talk will present detailed algorithmic approaches to approximating long-range electrostatics on GPUs and optimizing performance for molecular dynamics, the simulation of molecules. ...Read More
This talk will present detailed algorithmic approaches to approximating long-range electrostatics on GPUs and optimizing performance for molecular dynamics, the simulation of molecules. GPU implementations of these algorithms differ significantly from CPU implementations both in terms of the relative costs of computation versus memory access and in maximizing data parallelization. To this end, we will describe the Generalized Born method as it was implemented both for Folding@Home and for AMBER, as well as the implementation of the Particle Mesh Ewald (PME) method as implemented for AMBER, focusing on their implementations, and describing the tricks and tradeoffs required to achieve both accuracy and performance. Finally, we will describe how to extend these algorithms to multiple GPUs.  Back
 
Keywords:
Life & Material Science, Molecular Dynamics, GTC Silicon Valley 2009 - ID S09433
Streaming:
Download:
Molecular Dynamics
Presentation
Media
Short-Range Molecular Dynamics on GPU
Peng Wang
- NVIDIA
Learn how to accelerate short-range molecular dynamics using CUDA C. We will cover building the neighbor list and calculating the forces on the GPU. ...Read More
Learn how to accelerate short-range molecular dynamics using CUDA C. We will cover building the neighbor list and calculating the forces on the GPU. To handle the case where a few particles have significantly more neighbors than most other particles, we propose a hybrid data structure for the neighbor list that can achieve a good balance between performance and storage efficiency. A CUDA C implementation of the technique for Leonard-Jones forces can be found in the LAMMPS molecular dynamics open source code.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2010 - ID 2006
Streaming:
Download:
 
Simulations of Large Membrane Regions
Michela Taufer, Narayan Ganesan, Sandeep Patel
- University of Delaware
Learn how to study membrane-bound protein receptors by moving beyond the current state-of-the-art simulations that only consider small patches of physiological membranes. ...Read More
Learn how to study membrane-bound protein receptors by moving beyond the current state-of-the-art simulations that only consider small patches of physiological membranes. Towards this end, this session presents how to apply large-scale GPU-enabled computations of extended phospholipid bilayer membranes using a GPU code based on the CHARMM force field for MD simulations. Our code enables fast simulations of large membrane regions in NVT and NVE ensembles and includes different methods for the representation of the electrostatic interactions, i.e., reaction force field and Ewald summation (PME) methods. Performance and scientific results for dimyristoylphosphatidylcholine (PC) based lipid bilayers are presented.   Back
 
Keywords:
Molecular Dynamics, HPC and AI, Physics Simulation, GTC Silicon Valley 2010 - ID 2035
Streaming:
Download:
 
NAMD, CUDA, and Clusters: Taking GPU Molecular Dynamics Beyond the Desktop
James Phillips
- University of Illinois
A supercomputer is only as fast as its weakest link. The highly parallel molecular dynamics code NAMD was one of the first codes to run on a GPU cluster when G80 and CUDA were introduced in 2007. ...Read More
A supercomputer is only as fast as its weakest link. The highly parallel molecular dynamics code NAMD was one of the first codes to run on a GPU cluster when G80 and CUDA were introduced in 2007. Now, after three short years, the Fermi architecture opens the possibility of new algorithms, simpler code, and easier optimization. Come learn the opportunities and pitfalls of taking GPU computing to the petascale.  Back
 
Keywords:
Molecular Dynamics, HPC and AI, Life & Material Science, Physics Simulation, GTC Silicon Valley 2010 - ID 2054
Streaming:
Download:
 
HOOMD-blue: Fast and Flexible Many-Particle Dynamics
Joshua Anderson
- University of Michigan
See the newest capabilities and performance enhancements in HOOMD-blue, a general-purpose many-particle dynamics application written for GPUs. ...Read More
See the newest capabilities and performance enhancements in HOOMD-blue, a general-purpose many-particle dynamics application written for GPUs. Speedups of 80-100x are attained for a wide range of simulation types. Topics for this presentation include an overview of HOOMD-blue, design and implementation details of the underlying algorithms, and a discussion on how generality is maintained without sacrificing performance.  Back
 
Keywords:
Molecular Dynamics, HPC and AI, Life & Material Science, Physics Simulation, GTC Silicon Valley 2010 - ID S102062
Streaming:
Download:
 
High Performance Molecular Simulation, Visualization, and Analysis on GPUs
John Stone
- University of Illinois at Urbana-Champaign
This talk will present recent successes in the use of GPUs to accelerate interactive visualization and analysis tasks on desktop computers, and batch-mode simulation and analysis jobs on GPU-accelerated HPC clusters. ...Read More
This talk will present recent successes in the use of GPUs to accelerate interactive visualization and analysis tasks on desktop computers, and batch-mode simulation and analysis jobs on GPU-accelerated HPC clusters. We''ll present Fermi-specific algorithms and optimizations and compare with those for other devices. We''ll also present performance and performance/watt results for NAMD molecular dynamics simulations and VMD analysis calculations on GPU clusters, and conclude with a discussion of ongoing work and future opportunities for GPU acceleration, particularly as applied to the analysis of petascale simulations of large biomolecular complexes and long simulation timescales.   Back
 
Keywords:
Molecular Dynamics, Developer - Algorithms, HPC and AI, Life & Material Science, GTC Silicon Valley 2010 - ID S102073
Streaming:
Download:
 
GPGPU DL_POLY
Gilles Civario
- ICHEC
Discover DL_POLY. 1. DL_POLY: an MD code ICHEC has ported to CUDA. The presentation especially focuses on the auto-tuning of the work distribution between CPU and GPU
Discover DL_POLY. 1. DL_POLY: an MD code ICHEC has ported to CUDA. The presentation especially focuses on the auto-tuning of the work distribution between CPU and GPU   Back
 
Keywords:
Molecular Dynamics, HPC and AI, GTC Silicon Valley 2010 - ID S102086
Streaming:
Download:
 
Interactive Molecular Dynamics for Nanomechanical and Nanochemical Experiments
Axel Kohlmeyer
- Institute for Computational Molecular Science, Temple University
Hear how the combination of GPU accelerated molecular dynamics simulation software, 3D TV displays, affordable haptic game controllers, and high performance molecular visualization is leading to new ways to study materials ...Read More
Hear how the combination of GPU accelerated molecular dynamics simulation software, 3D TV displays, affordable haptic game controllers, and high performance molecular visualization is leading to new ways to study materials and objects on the nanoscale. We will present the concept of an appliance for integrated virtual nanoscale experiments and challenges related to software and hardware.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2010 - ID S102168
Download:
 
Energy Evaluation of Rosetta Proteins Using CUDA
Will Kohut
- University of California, Davis
In this poster, we describe preliminary results using CUDA to accelerate the energy evaluation of proteins folded by the Rosetta software suite.
In this poster, we describe preliminary results using CUDA to accelerate the energy evaluation of proteins folded by the Rosetta software suite.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2010 - ID P10N01
Download:
 
GPU Accelerated Molecular Dynamics Algorithms for Soft Matter Systems using HOOMD-Blue
Carolyn Phillips
- University of Michigan
The rheological, thermodynamic, and self-assembly behavior of liquids, colloids, polymers, foams, gels, granular materials and biological systems are often studied in simulation by using coarse-grained models based on molecular dynamics algorithms. ...Read More
The rheological, thermodynamic, and self-assembly behavior of liquids, colloids, polymers, foams, gels, granular materials and biological systems are often studied in simulation by using coarse-grained models based on molecular dynamics algorithms. The open source general purpose particle dynamics code HOOMD-Blue has been expanded to include the simulation techniques and pair potentials used to study this class of problems.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2010 - ID P10N02
Download:
 
Accelerating Molecular Modeling using GPUs
Wuchun Feng
- Virginia Tech
Computing electrostatic interactions in a biomolecule contributes towards the understanding of its structure and function, e. ...Read More
Computing electrostatic interactions in a biomolecule contributes towards the understanding of its structure and function, e.g., ligand binding, complex formation, and proton transport. However, such calculations on a desktop computer can take on the order of days, or even weeks, to run. Consequently, scientists seek to either reduce the algorithmic complexity, massively accelerate the computation with a GPU, or both. Our approach, based on an analytical linearized Poisson Boltzmann algorithm, delivers a 120-fold speed-up on a GPU (vs. a CPU-optimized -O3 with hand-tuned SSE). When combined with our hierarchical charge partitioning (HCP) multiscale method, however, the delivered speed-up approaches 20,000-fold.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2010 - ID P10N03
Download:
 
Faster, Cheaper, Better: Biomolecular Simulation with NAMD, VMD, and CUDA
John Stone
- University of Illinois at Urbana-Champaign
 
Keywords:
Molecular Dynamics, Life & Material Science, Supercomputing 2010 - ID SC1004
Download:
 
Accelerating Molecular Modeling Applications with GPU Computing
John Stone
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign
 
Keywords:
Molecular Dynamics, Life & Material Science, Supercomputing 2009 - ID SC0904
Streaming:
Download:
 
Achievements and Challenges for Stream Computing in Molecular Simulation
Erik Lindahl
 
Keywords:
Molecular Dynamics, Supercomputing 2011 - ID SC106
Streaming:
Download:
 
Ross Walker
 
Keywords:
Molecular Dynamics, Supercomputing 2011 - ID SC130
Streaming:
 
GPU-Based Molecular Dynamic Simulations Optimized with CUDPP and CURAND Libraries
Tyson Lipscomb (Wake Forest University)
Computer simulations are indispensible tools for deciphering how biomolecular structures and folding correspond to functions. These simulations benefit greatly from advances in parallel computations (e.g., GPUs) because the calculated forces are ...Read More

Computer simulations are indispensible tools for deciphering how biomolecular structures and folding correspond to functions. These simulations benefit greatly from advances in parallel computations (e.g., GPUs) because the calculated forces are inherently independent computations. However, a major limitation of GPUs is that the transfer of data between the CPU and GPU must be minimized. We introduce a new algorithm for calculating neighbor lists and transferring them to GPUs with minimal memory transfer. This algorithm is readily implemented with CUDPP and CURAND libraries. Using simulations of the ribosome, we observe a significant improvement in the performance, which is system size dependent.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID P2173
Download:
 
Plane Wave Pseudopotential Density Functional Theory Calculations on GPU Clusters
WeiLe Jia (Supercomputing Center of CNIC & Chinese Academy of Sciences)
In this poster, we present our implementation of the density functional theory (DFT) plane wave pseudo-potential (PWP) calculation on GPU clusters. This GPU version is developed based on a CPU DFT-PWP code: PEtot. Our test indicates that the GPU ...Read More

In this poster, we present our implementation of the density functional theory (DFT) plane wave pseudo-potential (PWP) calculation on GPU clusters. This GPU version is developed based on a CPU DFT-PWP code: PEtot. Our test indicates that the GPU version can have a ~10 times speed-up over the CPU version and is about 5 times faster than the legendary VASP code. An analysis of the speed-up and the scaling on the number of CPU/GPU computing units(up to 256) are presented. The success of our speed-up relies on a hybrid reciprocal-space and band-index parallelization scheme.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID P2174
Download:
 
Towards Routine Microsecond Molecular Dynamics Simulations on Commodity Hardware
Ross Walker (University of California San Diego)
The original AMBER 11 provided performance on one GPU equivalent to an 8 node cluster and almost 60ns/day for 8 GPUs running the JAC production benchmark without additional approximations outstripping the performance of all conventional supercom ...Read More

The original AMBER 11 provided performance on one GPU equivalent to an 8 node cluster and almost 60ns/day for 8 GPUs running the JAC production benchmark without additional approximations outstripping the performance of all conventional supercomputers. Here we describe further optimization of the code, coupled with hardware and software advances on the part of NVIDIA, that provides performance of >50ns/day on a single GPU with multiple GPUs providing simulation rates on systems the size of DHFR approaching a microsecond per day. This brings performance levels on desktops and commodity hybrid clusters to levels previously only considered possible using custom silicon.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2010
Streaming:
Download:
 
GPU-Accelerated Molecular Dynamics Simulation of Solid Covalent Crystals
Wei Ge (Institute of Process Engineering, Chinese Academy of Sciences)
An efficient and highly scalable algorithm for molecular dynamics (MD) simulation (using sophisticated many-body potentials) of solid covalent crystals is presented. Its effective memory throughput on a single C2050 GPU board reached 102 GB/s (8 ...Read More

An efficient and highly scalable algorithm for molecular dynamics (MD) simulation (using sophisticated many-body potentials) of solid covalent crystals is presented. Its effective memory throughput on a single C2050 GPU board reached 102 GB/s (81% of the peak), the instruction throughput reached 412 Ginstr/s (80% of the peak), and 27% of the peak flops of a single GPU was obtained. Parallel efficiency of the algorithm can be as high as 95% on all 7168 GPUs of Tianhe-1A, reaching possibly a record in high performance of MD simulations, 1.87Pflops in single precision.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2057
Streaming:
Download:
 
Advancing GPU Molecular Dynamics: Rigid Bodies in HOOMD-blue
Joshua Anderson (University of Michigan)
Learn how rigid body dynamics are implemented in HOOMD-blue. Previous releases were capable of executing classical molecular dynamics -- where free particles interact via smooth potentials and their motion through time is computed using Newton&# ...Read More

Learn how rigid body dynamics are implemented in HOOMD-blue. Previous releases were capable of executing classical molecular dynamics -- where free particles interact via smooth potentials and their motion through time is computed using Newton's laws. The latest version allows particles to be grouped into bodies that move as rigid units. Users can now simulate materials made of cubes, rods, bent rods, jacks, plates, patchy particles, bucky balls, or any other arbitrary shapes. This talk covers how these algorithms are implemented on the GPU, tuned to perform well for bodies of any size, and discusses several use-cases relevant to research.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2058
Streaming:
Download:
 
An Innovative Massively Parallelized Molecular Dynamic Software
Thomas Guignon (IFPEN)
In this paper, we present how we improved the speedup of the electronic structure calculator VASP by more than an order of magnitude. Recently, the research works done (at IFP Energies Nouvelles) have shown that by coupling traditional clusters ...Read More

In this paper, we present how we improved the speedup of the electronic structure calculator VASP by more than an order of magnitude. Recently, the research works done (at IFP Energies Nouvelles) have shown that by coupling traditional clusters or High Performance Computing (HPC) machines with accelerators based on graphical processor units (GPUs), by recording the most time consuming parts of the codes (with programming languages like CUDA, OpenCL) and offloading them on the graphic chips, it is possible to reduce the computing time to ensure a speedup of a factor of 5 to 15.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2108
Streaming:
Download:
 
Computational Screening of Novel Carbon Capture Materials
Jihan Kim (Berkeley Lab), Berend Smit (UC Berkeley/Berkeley Lab)
Discover how GPUs are used to identify optimal framework structures for carbon dioxide separation with the goal of reducing carbon emission. We describe the algorithm behind our GPU software tool that iterates through a database of hypothetical ...Read More

Discover how GPUs are used to identify optimal framework structures for carbon dioxide separation with the goal of reducing carbon emission. We describe the algorithm behind our GPU software tool that iterates through a database of hypothetical zeolites and computes the selectivity of each of the structures. The code can be easily extended to simulate other adsorbent structures such as ZIFs (zeolitic imidazolate frameworks) and provide valuable insights to both theorists and experimentalists who have interest in carbon capture research.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2122
Streaming:
Download:
 
Petascale Molecular Dynamics Simulations on GPU-Accelerated Supercomputers
James Phillips (University of Illinois at Urbana-Champaign)
The highly parallel molecular dynamics code NAMD was chosen in 2006 as a target application for the NSF petascale supercomputer now know as Blue Waters. NAMD was also one of the first codes to run on a GPU cluster when G80 and CUDA were introduc ...Read More

The highly parallel molecular dynamics code NAMD was chosen in 2006 as a target application for the NSF petascale supercomputer now know as Blue Waters. NAMD was also one of the first codes to run on a GPU cluster when G80 and CUDA were introduced in 2007. How do the Cray XK6 and modern GPU clusters compare to 300,000 CPU cores for a hundred-million-atom Blue Waters acceptance test? Come learn the opportunities and pitfalls of taking GPU computing to the petascale and the importance of CUDA 4.0 features in combining multicore host processors and GPUs in a legacy message-driven application.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2127
Streaming:
Download:
 
GPU-Based Molecular Dynamics Simulations of Protein and RNA Assembly
Samuel Cho (Wake Forest University)
Protein and RNA biomolecular folding and assembly problems have important applications because misfolding is associated with diseases like Alzheimer's and Parkinson's. However, simulating complex biomolecules on the same timescales as ex ...Read More

Protein and RNA biomolecular folding and assembly problems have important applications because misfolding is associated with diseases like Alzheimer's and Parkinson's. However, simulating complex biomolecules on the same timescales as experiments is an extraordinary challenge due to a bottleneck in the force calculations. To overcome these hurdles, we perform coarse-grained molecular dynamics simulations where biomolecules are reduced into simpler components. Furthermore, our GPU-based simulations have a significant performance improvement over CPU-based simulations, which is limited to systems of 50-150 residues/nucleotides. The GPU-based code can simulate protein/RNA systems of 400-10,000+ residues/nucleotides, and we present ribosome assembly simulations.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2139
Streaming:
Download:
 
VMD: High Performance Molecular Visualization and Analysis on GPUs
John Stone (University of Illinois at Urbana-Champaign)
This talk will present recent successes in the use of GPUs to accelerate interactive molecular visualization and analysis tasks on desktop computers, and batch-mode simulation and analysis jobs on GPU-accelerated HPC clusters. We'll present ...Read More

This talk will present recent successes in the use of GPUs to accelerate interactive molecular visualization and analysis tasks on desktop computers, and batch-mode simulation and analysis jobs on GPU-accelerated HPC clusters. We'll present Fermi-specific algorithms and optimizations and compare with those for other devices. We'll also present performance and performance/watt results for VMD analysis calculations on GPU clusters, and conclude with a discussion of ongoing work and future opportunities for GPU acceleration, particularly as applied to the analysis of petascale simulations of large biomolecular complexes and long simulation timescales.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2142
Streaming:
Download:
 
A Study of Persistent Threads Style Programming Model for GPU Computing
Kshitij Gupta (UC Davis), Jeff Stuart (UC Davis)
We present the usefulness of a new style of GPU programming called Persistent Threads, known to be useful on irregular workloads. First, we will begin by formally defining the PT model. We will then categorize use of PT into four "use cases ...Read More

We present the usefulness of a new style of GPU programming called Persistent Threads, known to be useful on irregular workloads. First, we will begin by formally defining the PT model. We will then categorize use of PT into four "use cases", and present micro-benchmark analyses of when this model is useful over traditional kernel formulations. Third, we will show a full speech recognition application that uses all four PT use cases. Finally, we will conclude our talk by suggesting appropriate modifications to GPU hardware, software, and APIs that make PT kernels both easier to implement and more efficient.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2157
Streaming:
Download:
 
Terascale Volume Visualization in Neuroscience
Johanna Beyer (KAUST), Markus Hadwiger (KAUST)
Learn how to create a scalable volume visualization system for interactive rendering of terascale EM data. We will describe the major design principles, how we can avoid the standard approach of pre-computing a 3D multi-resolution hierarchy such ...Read More

Learn how to create a scalable volume visualization system for interactive rendering of terascale EM data. We will describe the major design principles, how we can avoid the standard approach of pre-computing a 3D multi-resolution hierarchy such as an octree, and how to handle continuous streaming of newly acquired data. For rendering we build upon a visibility-driven approach and 3D virtual texturing, and perform interactive volume rendering of a "virtual" volume, where the corresponding physical storage is only represented and populated in a sparse manner with 2D instead of 3D image data on the fly during rendering.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2202
Streaming:
Download:
 
GPU Enabled Macromolecular Simulation: Challenges and Opportunities
Michela Taufer (University of Delaware), Sandeep Patel (University of Delaware)
GPU enabled simulation of fully atomistic macromolecular simulation is rapidly gaining momentum, enabled by the massive parallelism and due to parallelizability of various components of the underlying algorithms and methodologies. The massive pa ...Read More

GPU enabled simulation of fully atomistic macromolecular simulation is rapidly gaining momentum, enabled by the massive parallelism and due to parallelizability of various components of the underlying algorithms and methodologies. The massive parallelism in the order of several hundreds to few thousands of cores, presents opportunities as well poses implementation challenges. In this talk dive deep into the various key aspects of simulation methodologies of macro molecular systems specifically adapted to GPUs. Learn some of the underlying challenges and get the latest solutions devised to tackle them in the FEN ZI code for fully atomistic macromolecular simulations.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2207
Streaming:
Download:
 
Probing Bio-Nano Interface Structure from Microsecond Molecular Dynamics on GPUs
Olexandr Isayev (Case Western Reserve University)
Using the latest algorithmic development in molecular dynamics on multiple GPUs over MPI, and technologies like GPUDirect it is now possible to address problems of interaction at bio-nano interface via large scale atomistic simulations. This tal ...Read More

Using the latest algorithmic development in molecular dynamics on multiple GPUs over MPI, and technologies like GPUDirect it is now possible to address problems of interaction at bio-nano interface via large scale atomistic simulations. This talk will discuss the aspects of DNA-nanotube interactions and SWCNT induced conformational changes in DNA nucleosome structure. We will also address technical challenges upon porting and tuning AMBER 11 code on Condor GPU cluster at AFRL.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2315
Streaming:
Download:
 
Strong Scaling for Molecular Dynamics Applications
Sarah Tariq (NVIDIA)
In this session we will talk about how to improve strong scaling for molecular dynamics applications. Using the NAMD molecular dynamics code as our primary case study, we will discuss the types of issues that can impede scaling, how to use alrea ...Read More

In this session we will talk about how to improve strong scaling for molecular dynamics applications. Using the NAMD molecular dynamics code as our primary case study, we will discuss the types of issues that can impede scaling, how to use already available and custom tools to discover such issues, and how to build a model to help analyze and predict scaling performance. Although this session is primarily focused on molecular dynamics applications, most of the lessons can be applied equally well to many other areas and applications.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2351
Streaming:
Download:
 
Efficient Molecular Dynamics on Heterogeneous GPU Architectures in GROMACS
Molecular Dynamics is an important application for GPU acceleration, but many algorithmic optimizations and features still rely on code that prefers traditional CPUs. It is only with the latest hardware and software we have been able to realize ...Read More

Molecular Dynamics is an important application for GPU acceleration, but many algorithmic optimizations and features still rely on code that prefers traditional CPUs. It is only with the latest hardware and software we have been able to realize a heterogeneous GPU/CPU implementation and reach performance significantly beyond the state-of-the-art of hand-tuned CPU code in our GROMACS program. The sub-millisecond iteration time poses challenges on all levels of parallelization. Come and learn about our new atom-cluster pair interaction approach for non-bonded force evaluation that achieves 60% work-efficiency and other innovative solutions for heterogeneous GPU systems.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2363
Streaming:
Download:
 
Molecule Dynamics, GPUs, and EC2 (Presented by Amazon)
Scott Le Grand (Amazon Web Services)
GPUs have made molecular dynamics simulations faster, better, and cheaper, achieving supercomputer performance from a single GPU without sacrificing stability or accuracy. In this talk we demonstrate how the GPU refactoring of AMBER 12 Molecular ...Read More

GPUs have made molecular dynamics simulations faster, better, and cheaper, achieving supercomputer performance from a single GPU without sacrificing stability or accuracy. In this talk we demonstrate how the GPU refactoring of AMBER 12 Molecular Dynamics has led to an implementation that produces results that are indistinguishable from the original CPU code. In addition, we describe the GPU compute instances available on the Amazon EC2 platform to show how anyone can run any number of AMBER 12 simulations, anytime from anywhere.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID S2644
Streaming:
Download:
 
Single vs. Double Precision MD Simulations: Correlation is Length-Scale Dependent
Anqi Zou (Wake Forest University)
This poster evaluates how single vs. double precision operations affect Molecular Dynamics simulations using a GPU-optimized MD simulation software by performing coarse-grained MD simulations of many biologically relevant systems of various size. Thr ...Read More
This poster evaluates how single vs. double precision operations affect Molecular Dynamics simulations using a GPU-optimized MD simulation software by performing coarse-grained MD simulations of many biologically relevant systems of various size. Three different measures of structural similarity are used to analyze structure of trajectories and to determine when single precision calculations would be appropriate and when would not. The conclusion is that the increased performance of single-precision implementations of MD simulations makes no significant difference in the accuracy and precision of MD simulations if the system size is sufficiently large.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID P2443
Download:
 
GPU-Based Monte Carlo Simulations for Canonical and Gibbs Ensembles
Loren Schwiebert (Wayne State University)
Markov Chain Monte Carlo (MCMC) simulation of chemical systems allows examination of nanoscopic thermodynamics and associated behavior at small time scales. These simulations tend to be computationally expensive, requiring days or more of CPU ti ...Read More

Markov Chain Monte Carlo (MCMC) simulation of chemical systems allows examination of nanoscopic thermodynamics and associated behavior at small time scales. These simulations tend to be computationally expensive, requiring days or more of CPU time to collect data. Optimization work is essential in order to remedy the inherent time complexity of these simulations. To date, there is no multi-ensemble molecular MCMC engine for the simulation of chemical systems that leverages GPUs. A speed up of 6.3 and 14.4 times were achieved for a problem size of 131072 particles for the canonical and Gibbs ensemble implementations, respectively.

  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID P2453
Download:
 
Simultaneous Evolution of Multiple Molecular Dynamics Simulations
Cory Slep (NC State University)
The need to generate statistically significant data from time intensive molecular dynamics (MD) simulations drives the search for algorithms that can take advantage of inherent parallelism in computer architectures. CUDA is an ideal platform for perf ...Read More
The need to generate statistically significant data from time intensive molecular dynamics (MD) simulations drives the search for algorithms that can take advantage of inherent parallelism in computer architectures. CUDA is an ideal platform for performing multiple MD simulations for ensemble averaging. We demonstrate a proof of concept highlighting the potential of CUDA in performing multiple MD simulations with different initial conditions. Compared to the traditional implementation, CUDA is able to deliver the output ten times faster. Work is in progress for improving the performance through memory optimization.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID P2456
Download:
 
GPU Accelerated Molecular Dynamics Enabling Transformative Drug Development
Benjamin Madej (University of California San Diego, San Diego Supercomputer Center)
One powerful computational technique for the science of drug development has been the use of molecular dynamics (MD) simulations. MD simulations can explore the interactions between small molecule drugs and membrane-bound proteins on an atomic level. ...Read More
One powerful computational technique for the science of drug development has been the use of molecular dynamics (MD) simulations. MD simulations can explore the interactions between small molecule drugs and membrane-bound proteins on an atomic level. It is now possible to understand the biological function of drug targets through their structural motions. GPU computing is revolutionizing the field of MD, with GPU accelerated MD code competing with national supercomputers. Our research goal is to use GPU technology to not only improve MD performance, but to improve MD development and workflow for drug development.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2012 - ID P2539
Download:
 
GPU-enabled Macromolecular Simulation: Challenges and Opportunities
Michela Taufer (Department of Computer and Information Sciences, University of Delaware)
GPU-enabled simulation of fully atomistic macromolecular simulation is rapidly gaining momentum, enabled by the massive parallelism and due to parallelizability of various components of the underlying algorithms and methodologies. The massive pa ...Read More

GPU-enabled simulation of fully atomistic macromolecular simulation is rapidly gaining momentum, enabled by the massive parallelism and due to parallelizability of various components of the underlying algorithms and methodologies. The massive parallelism, in the order of several hundred to a few thousand cores, presents opportunities as well as poses implementation challenges. In this webinar, Michela Taufer, Assistant Professor, Department of Computer and Information Sciences, University of Delaware, discusses various key aspects of simulation methodologies of macro molecular systems specifically adapted to GPUs. She will also visit some of the underlying challenges and solutions devised to tackle them.

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2011 - ID GTCE007
Streaming:
Download:
 
Molecular Dynamics with LAMMPS on a Hybrid Cray Supercomputer
Michael Brown (National Center for Computational Sciences, Oak Ridge National Laboratory)
We present software development efforts in LAMMPS that allow for acceleration with GPUs on supercomputers. We present benchmark results for solid-state, biological and mesoscopic systems along with results from simulation of liposomes, polyelect ...Read More

We present software development efforts in LAMMPS that allow for acceleration with GPUs on supercomputers. We present benchmark results for solid-state, biological and mesoscopic systems along with results from simulation of liposomes, polyelectrolyte brushes, and copper nanostructures on graphite. We present methods for efficient simulation with GPUs at larger node counts.

  Back
 
Keywords:
Molecular Dynamics, Supercomputing 2012 - ID SC2024
Download:
 
GALAMOST: GPU-accelerated Large-scale Molecular Simulation Toolkit
You-Liang Zhu (Institute of Theoretical Chemistry, Jilin University)
GALAMOST is a versatile molecular simulation package designed to utilize the computational power of graphics processing units (GPUs) as much as possible. Besides the basic functions of molecular dynamics packages, it is developed specially for the st ...Read More
GALAMOST is a versatile molecular simulation package designed to utilize the computational power of graphics processing units (GPUs) as much as possible. Besides the basic functions of molecular dynamics packages, it is developed specially for the studies of the self-assembly, phase transition, and other properties of polymeric systems aiming at mesoscopic scale by employing some latest simulation methods. Our package contains a hybrid particle-field molecular dynamics technique, an iterative Boltzmann inversion numerical potential method, a soft anisotropic particle model, and a chain-growth polymerization model. With these well-developed methods in recent years and their implementation on a single GPU by GALAMOST, the coarse-graining simulations for polymers can be performed with very large system sizes over long simulated time.  Back
 
Keywords:
Molecular Dynamics, Computational Physics, GTC Silicon Valley 2013 - ID P3142
Download:
 
Efficient GPU-accelerated Molecular Dynamics Simulation with Load Balancing
Takuro Udagawa (Tokyo Institute of Technology)
These days, more and more PC clusters have adopted GPUs and a lot of applications including Molecular Dynamics are implemented for GPUs use. Although GPUs have accelerated those applications, low CPU utilization have been observed in some applicat ...Read More
These days, more and more PC clusters have adopted GPUs and a lot of applications including Molecular Dynamics are implemented for GPUs use. Although GPUs have accelerated those applications, low CPU utilization have been observed in some applications. In this study, we proposed a CPU-GPU load balancing method for a molecular dynamics simulation and evaluated the performance improvement. Our method accelerated the simulation about 20% at the most.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2013 - ID P3161
Download:
 
GPU Accelerated Design of Peptide Nucleic Acid Conjugates for Oncogene Imaging
Matthew Wampole (Thomas Jefferson University)
This poster explores the use of GPU accelerated molecular dynamics to study the binding for Peptide Nucleic Acids with RNA. The development of tumor specific imaging probes could lead to patient screenings to determine how successful a treatment will ...Read More
This poster explores the use of GPU accelerated molecular dynamics to study the binding for Peptide Nucleic Acids with RNA. The development of tumor specific imaging probes could lead to patient screenings to determine how successful a treatment will be. Synthesizing and analyzing these probes can be costly and time consuming processes. We have developed new force fields for PNAs, including a modified hypoxanthine base, and are testing the newly released accelerated Molecular Dynamics in Amber 12. Our goal is to develop a computational pipeline to determine how effective our PNA constructs will be at binding to mutant RNA sequences.   Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2013 - ID P3243
Download:
 
AMBER and Kepler GPUs
Ross Walker (Assistant Research Professor, University of California, San Diego)
This webinar showcases the latest GPU-acceleration technologies available to AMBER users and discusses features, recent updates and future plans. Join us to learn how to obtain the latest accelerated versions of AMBER, which features are su ...Read More

This webinar showcases the latest GPU-acceleration technologies available to AMBER users and discusses features, recent updates and future plans. Join us to learn how to obtain the latest accelerated versions of AMBER, which features are supported, the simplicity of its installation and use, and how it performs with Kepler GPUs.

 

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2013 - ID GTCE029
 
Gromacs and Kepler GPUs
Erik Lindahl (Professor, Stockholm University)
Learn about the first multi-node, multi-GPU-enabled release 4.6 of GROMACS from Dr. Erik Lindahl, the project leader for this popular molecular dynamics package. GROMACS 4.6 allows you to run your models up to 3X faster compare to the latest sta ...Read More

Learn about the first multi-node, multi-GPU-enabled release 4.6 of GROMACS from Dr. Erik Lindahl, the project leader for this popular molecular dynamics package. GROMACS 4.6 allows you to run your models up to 3X faster compare to the latest state-of-the-art parallel AVX-accelerated CPU-code in GROMACS. Dr. Lindahl will talk about the new features of the latest GROMACS 4.6 release as well as future plans. You will learn how to download the latest accelerated version of GROMACS and which features are GPU supported. Dr. Lindahl will cover GROMACS performance on the very latest NVIDIA Kepler hardware and explain how to run GPU-accelerated MD simulations. You will also be invited to try GROMACS on K20 with a free test drive and experience all the new features and enhanced performance for yourself: http://www.nvidia.com/gputestdrive 

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2013 - ID GTCE030
 
Molecular Shape Searching on GPUs: A Brave New World
Paul Hawkins (Applications Science Group Leader, OpenEye)
Shape is a fundamental three dimensional molecular property and a powerful descriptor for molecular comparison and similarity assessment; similarity in shape has proven to be a very effective method for predicting similarity in biology. As such ...Read More

Shape is a fundamental three dimensional molecular property and a powerful descriptor for molecular comparison and similarity assessment; similarity in shape has proven to be a very effective method for predicting similarity in biology. As such shape-based virtual screening (searching a database of molecules for those compounds that are similar in shape to a molecule with desirable biological activity) has become an integral part of computational drug discovery, due to both its speed and efficacy.OpenEye’s recent port of their shape similarity application, ROCS, to the GPU has resulted in a virtual screening tool of unprecedented power – FastROCS. FastROCS’ speed allows it to perform large-scale calculations of a kind inaccessible in the past (shape comparisons of millions of molecules to one another) and has accelerated more routine shape searching to the point that it has become competitive with more traditional, but less effective, two dimensional methods. Join Paul Hawkins, Applications Science Group Leader at OpenEye, as he presents some recent performance data on FastROCS on NVIDIA hardware and discusses some of the new applications that this speed has enabled.You will also be invited to take the Tesla K20 for a free test drive and experience all the new features and enhanced performance for yourself: www.nvidia.com/gputestdrive.

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2013 - ID GTCE032
 
Uncovering the Elusive HIV Capsid with Kepler GPUs Running NAMD and VMD
Dr. Juan R. Perilla (University of Illinois at Urbana–Champaign)
Join Dr. Juan R. Perilla and learn how in a tour de force effort, experimental and computational scientists at the University of Illinois at Urbana–Champaign and the University of Pittsburg have now resolved the HIV capsid's chemical s ...Read More

Join Dr. Juan R. Perilla and learn how in a tour de force effort, experimental and computational scientists at the University of Illinois at Urbana–Champaign and the University of Pittsburg have now resolved the HIV capsid's chemical structure. As reported recently on the cover of Nature, the researchers combined NMR structure analysis, electron microscopy and data-guided molecular dynamics simulations utilizing VMD to prepare and analyze simulations performed using NAMD on NVIDIA GPUs in one of the most powerful computers worldwide, Blue Waters, to obtain and characterize the HIV-1 capsid. The discovery can now guide the design of novel drugs for enhanced antiviral therapy.Also learn how NAMD performs with the latest Kepler GPUs, as well as details about GPU Test Drive (www.nvidia.com/GPUTestDrive) and how to try NAMD on Kepler GPUs for free.

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2013 - ID GTCE041
Streaming:
Download:
 
ACEMD: High-throughput Molecular Dynamics with NVIDIA Kepler GPUs
Matt Harvey (Acellera), Gianni Fabritiis (Acellera)
Join Acellera Founder, Gianni De Fabritiis, and CTO, Matt Harvey, to learn about the latest developments of high-throughput molecular dynamics both in terms of applications and methodological advances. Examples will be given in the context of AC ...Read More

Join Acellera Founder, Gianni De Fabritiis, and CTO, Matt Harvey, to learn about the latest developments of high-throughput molecular dynamics both in terms of applications and methodological advances. Examples will be given in the context of ACEMD, a highly efficient, best-in-class graphical processing units (GPUs) centric code for running MD simulations, and its protocols. In particular, attendees will learn how the high arithmetic performance and intrinsic parallelism of the latest NVIDIA Kepler GPUs can offer a technological edge for molecular dynamics simulations. Micro to milliseconds molecular dynamics on accelerator hardware which will have important methodological and scientific implications will be highlighted. This webinar presents a great opportunity for industrial scientists to get an overview of the current achievements in molecular simulations for medicinal chemistry.

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2013 - ID GTCE043
Streaming:
Download:
 
Using GPUs to Supercharge Visualization and Analysis of Molecular Dynamics Simulations with VMD
John Stone (University of Illinois)
VMD is a tool for preparing, analyzing, and visualizing molecular dynamics simulations, with particular emphasis on large biomolecular systems, including drug targets such as the bacterial ribosome, and large viruses such as HIV.The computationa ...Read More

VMD is a tool for preparing, analyzing, and visualizing molecular dynamics simulations, with particular emphasis on large biomolecular systems, including drug targets such as the bacterial ribosome, and large viruses such as HIV.The computational challenges posed by large simulations present a significant hurdle for simulation and analysis tools. GPUs provide unprecedented computational capabilities at a very low cost, making it possible for applications like VMD to accelerate tasks that would otherwise be beyond our grasp. The ubiquitous nature of powerful GPUs on hardware ranging from tablets to supercomputers has allowed us to make a significant investment in developing GPU algorithms for a broad range of uses covering everything from ion placement during simulation preparation to photorealistic ray tracing of movies on hundreds of supercomputer nodes.Join us for this webinar as John Stone, Senior Research Programmer, University of Illinois provides an overview of the GPU-accelerated features of VMD and how they can be used to speed up a wide range of simulation preparation, analysis, and visualization tasks today, along with a roadmap of things to come in the future. 

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2014 - ID GTCE075
Streaming:
Download:
 
An Overview of AMBER 14
Ross Walker (University of California San Diego), Adrian Roitberg (University of Florida)
This webinar will provide an overview of the AMBER Molecular Dynamics Software package with focus on what is new with regards to GPU acceleration in the recently released version 14. This includes details of peer-to-peer support and optimization ...Read More

This webinar will provide an overview of the AMBER Molecular Dynamics Software package with focus on what is new with regards to GPU acceleration in the recently released version 14. This includes details of peer-to-peer support and optimizations, which have resulted in version 14 being the fastest MD software package on commodity hardware. Benchmarks will be provided, along with recommended hardware choices. In addition, an overview of the new GPU centric features in AMBER 14 will be covered, including support for multi-dimensional replica exchange MD, hydrogen mass repartitioning, accelerated MD, Scaled MD, and support-as-a-service on Amazon Web Services. This is a joint webinar by Ross C. Walker, University of California San Diego and Adrian Roitberg, University of Florida. 

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2014 - ID GTCE081
Streaming:
Download:
 
OpenMM Molecular Dynamics on Kinases: Key Cancer Drug Targets Revealed with New Methods and GPU Clusters
Vijay Pande (Stanford University)
Learn how to use GPU-enabled molecular dynamics codes, parallelized on a cluster of 100 GPUs, and sample key conformational transitions. When applied to protein kinase molecules, key targets in anti-cancer drugs, these methods reveal new insights in ...Read More
Learn how to use GPU-enabled molecular dynamics codes, parallelized on a cluster of 100 GPUs, and sample key conformational transitions. When applied to protein kinase molecules, key targets in anti-cancer drugs, these methods reveal new insights into how to target new drugs to these systems.  Back
 
Keywords:
Molecular Dynamics, Big Data Analytics, Bioinformatics & Genomics, Computational Physics, GTC Silicon Valley 2014 - ID S4133
Streaming:
 
Heterogeneous CPU+GPU Molecular Dynamics Engine in CHARMM
Antti-Pekka Hynninen (National Renewable Energy Laboratory)
This presentation provides a first glimpse of a heterogeneous CPU+GPU Molecular Dynamics (MD) engine in CHARMM. In the MD engine, the GPU is used for the calculation of the direct part of the non-bonded force calculation, while the CPU takes care of ...Read More
This presentation provides a first glimpse of a heterogeneous CPU+GPU Molecular Dynamics (MD) engine in CHARMM. In the MD engine, the GPU is used for the calculation of the direct part of the non-bonded force calculation, while the CPU takes care of the rest of the work (reciprocal force calculation, bonded force calculation, integration, etc.). The MD engine is built around the CHARMM domain decomposition code enabling massively parallel MD simulations on multiple CPU+GPU nodes. The new MD engine outperforms the CPU code by a factor of 8 or more.  Back
 
Keywords:
Molecular Dynamics, Numerical Algorithms & Libraries, Computational Physics, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4163
Streaming:
Download:
 
OpenMM: GPU Accelerated Algorithm Development for Molecular Dynamics
Peter Eastman (Stanford University)
Learn how to develop molecular dynamics algorithms for a GPU without writing any GPU code. OpenMM provides a high level scripting language in which scientists describe the computation to do using mathematics, not code. The equations are automatical ...Read More
Learn how to develop molecular dynamics algorithms for a GPU without writing any GPU code. OpenMM provides a high level scripting language in which scientists describe the computation to do using mathematics, not code. The equations are automatically analyzed and transformed into highly optimized CUDA kernels. This happens at runtime and is invisible to the user. Entirely novel algorithms can be implemented in just a few lines by someone with no CUDA programming experience, yet they run at full speed on the GPU hardware. This talk will describe how to use OpenMM to dramatically simplify and accelerate MD algorithm development. It also will describe the techniques used to transform equations into optimized code, making it relevant to programmers who want to apply similar techniques to other fields.  Back
 
Keywords:
Molecular Dynamics, Computational Physics, GTC Silicon Valley 2014 - ID S4184
Streaming:
Download:
 
Deep Optimization of the Parallel Algorithm for Molecular Dynamics Simulations
Witold Rudnicki (University of Warsaw, ICM)
In-depth analysis of optimizations of the molecular dynamics code for large-scale molecular dynamics simulations will be presented. They were performed on the GPU port of the IMD code used for MD simulations of large solid-state systems. Several opt ...Read More
In-depth analysis of optimizations of the molecular dynamics code for large-scale molecular dynamics simulations will be presented. They were performed on the GPU port of the IMD code used for MD simulations of large solid-state systems. Several optimization techniques were developed for the linked-cell protocol of MD simulations: (1) tiling of atom-atom interactions; (2) implementation of action reaction principle; (3) removal of redundant atoms and tiles; and (4) pipelining of the computations for subsequent layers of cells. These methods were compared with a brute force approach and tested for Fermi and Kepler architectures. The optimizations employed allowed up to 5-fold performance improvement in comparison with the straightforward port on Kepler and up to 3-fold improvement on Fermi. Up to 60-fold speedups of force kernels were observed in comparison with a single core CPU. The single workstation with K20 card was equivalent to 64 MPI processes on a cluster.  Back
 
Keywords:
Molecular Dynamics, Computational Physics, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4295
Streaming:
 
GPU Accelerated Parallel Simulated Annealing for Fitting Molecular Dynamics Potentials
Pierre-Yves Taunay (The Pennsylvania State University)
This work presents a parallel simulated annealing implementation for fitting molecular dynamics potentials. In our implementation, each GPU is given a random set of Lennard-Jones parameters sigma and epsilon, and performs separately a molecular dynam ...Read More
This work presents a parallel simulated annealing implementation for fitting molecular dynamics potentials. In our implementation, each GPU is given a random set of Lennard-Jones parameters sigma and epsilon, and performs separately a molecular dynamics simulation. A derived quantity, the structure factor, is then compared to experimental data and determines the quality of the fitting parameters. Information about the best fit is exchanged across GPUs at a fixed number of iterations. The choice of random parameters is then restarted in the vicinity of the best parameter set. Using GPUs, a larger parameter set can be explored in a given time as molecular dynamics simulations benefit greatly from GPU acceleration.  Back
 
Keywords:
Molecular Dynamics, Numerical Algorithms & Libraries, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4307
Streaming:
 
Computing the Cure: Combining Sequencing and Physical Simulation on GPUs to Provide Patient Customized Cancer Treatments
Ross Walker (UCSD)
The sequencing revolution is completely changing the landscape of cancer treatment ushering in the era of personalized medicine where individual treatments will be customized for a specific patient. Instead of simply looking at stained tumor biopsy ...Read More
The sequencing revolution is completely changing the landscape of cancer treatment ushering in the era of personalized medicine where individual treatments will be customized for a specific patient. Instead of simply looking at stained tumor biopsy sections under a microscope, cancer diagnosis is going high-tech by allowing sequencing of patient tumors (and patient genomes) to determine what precise molecular events cause an individual cancer. In principle, this sequence information holds the key to individually targeted therapies with enormously increased success rates in treating (and even curing) cancer. This is the "molecular oncology" revolution and it will completely change the cancer diagnosis and treatment landscape in the next decade. This talk will highlight work by scientists at MSKCC, Stanford and UCSD to build the tools needed to determine drug susceptibilities using a combination of sequencing data and *physical* simulation. This work will ultimately provide a way to compute patient customized cancer treatments.  Back
 
Keywords:
Molecular Dynamics, Bioinformatics & Genomics, Computational Physics, Computational Structural Mechanics, GTC Silicon Valley 2014 - ID S4333
Streaming:
 
Visualization and Analysis of Petascale Molecular Simulations with VMD
John Stone (University of Illinois)
We present recent successes in the use of GPUs to accelerate challenging molecular visualization and analysis tasks on hardware platforms ranging from commodity desktop computers to the latest Cray XK7 supercomputers. This talk will focus on recent a ...Read More
We present recent successes in the use of GPUs to accelerate challenging molecular visualization and analysis tasks on hardware platforms ranging from commodity desktop computers to the latest Cray XK7 supercomputers. This talk will focus on recent algorithm developments and the applicability and efficient use of new CUDA features on state-of-the-art Kepler GPUs. We will present the latest performance results for GPU accelerated trajectory analysis runs on Cray XK7 petascale systems and GPU-accelerated workstation platforms. We will conclude with a discussion of ongoing work and future opportunities for GPU acceleration, particularly as applied to the analysis of petascale simulations of large biomolecular complexes and long simulation timescales.  Back
 
Keywords:
Molecular Dynamics, Big Data Analytics, Scientific Visualization, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4410
Streaming:
Download:
 
Peer-to-Peer Molecular Dynamics and You
Scott LeGrand (Amazon Web Services)
Recent code optimization within AMBER has improved single-node performance by up to 30% and multi-GPU scaling by up to 70%. The latter was achieved by aggressive use of Peer-to-Peer copies and RDMA. This has unleashed new time scale regimes for sam ...Read More
Recent code optimization within AMBER has improved single-node performance by up to 30% and multi-GPU scaling by up to 70%. The latter was achieved by aggressive use of Peer-to-Peer copies and RDMA. This has unleashed new time scale regimes for sampling and simulation on low-end GPU clusters, beating every known software-based molecular dynamics codebase in existence at the time of submission. This talk will cover first how AMBER's already efficient single-node performance was made even more so, the challenge not only of enabling peer to peer copies between GPUs, but obtaining hardware capable of enabling it, and finally, up to the minute results using MVAPICH2 and OpenMPI for RDMA directly between GPUs on separate nodes connected by dual-line FDR Infiniband.  Back
 
Keywords:
Molecular Dynamics, Big Data Analytics, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4460
Streaming:
Download:
 
Accelerating the Discrete Element Method for Faceted Particles Using HOOMD-Blue
Matthew Spellings (University of Michigan)
Explore the concepts behind large-scale modeling of faceted anisotropic particles. Dynamical methods are the most direct way to study the full set of properties of systems of colloidal and nanoscale particles. Classical and event-driven molecula ...Read More

Explore the concepts behind large-scale modeling of faceted anisotropic particles. Dynamical methods are the most direct way to study the full set of properties of systems of colloidal and nanoscale particles. Classical and event-driven molecular dynamics simulations of the past have focused on behavior of isotropic particles and limited classes of anisotropic particles such as ellipsoids. In this talk, we discuss the algorithms and data structures behind a GPU-accelerated implementation of the discrete element method for polyhedral particles in HOOMD-Blue. This formulation allows us to efficiently simulate conservative and non-conservative dynamics of faceted shapes within a classical molecular dynamics framework. Research applications include studies of nucleation and growth, granular materials, glassy dynamics and active matter.

  Back
 
Keywords:
Molecular Dynamics, Computational Physics, GTC Silicon Valley 2014 - ID S4477
Download:
 
GPU Accelerated Fully Flexible Haptic Protein-Ligand Docking
Thanasis Anthopoulos (Cardiff University)
This presentation refers to a haptic protein-ligand docking (HPLD) application developed in the Molecular Modelling Lab of the Cardiff School of Pharmacy. The talk aims to describe in detail how GPUs enabled the application to run with a fully flexib ...Read More
This presentation refers to a haptic protein-ligand docking (HPLD) application developed in the Molecular Modelling Lab of the Cardiff School of Pharmacy. The talk aims to describe in detail how GPUs enabled the application to run with a fully flexible ligand and protein target. The first part of the talk describes the algorithm used to perform the MMFF94s force-field energy and force calculations. Performance benchmarks will be presented to show the speed-up gained from the presented CUDA algorithms. The second part of the talk refers to an evolutionary algorithm designed to exploit Hyper-Q capabilities and evaluate asynchronously Energy kernels using the algorithm explained in the first part of the talk. Performance benchmarks are provided to show how the algorithm can achieve an additional 2-3X depending on system size when it runs on a GK110 chipset. The session closes with results generated from researchers using the CUDA version of the application.   Back
 
Keywords:
Molecular Dynamics, Computational Physics, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4492
Streaming:
Download:
 
Accelerating Dissipative Particle Dynamics Simulation on Kepler: Algorithm, Numerics and Application
Yu-Hang Tang (Brown University)
The talk focuses on the implementation of a highly optimized dissipative particle dynamics (DPD) simulation code in CUDA, which achieves 20 times speedup on a single Kepler GPU over 12 Ivy-Bridge cores. We will introduce a new pair searching algorith ...Read More
The talk focuses on the implementation of a highly optimized dissipative particle dynamics (DPD) simulation code in CUDA, which achieves 20 times speedup on a single Kepler GPU over 12 Ivy-Bridge cores. We will introduce a new pair searching algorithm that is parallel, deterministic, capable of generating strictly ordered neighbor list and atomics-free. Such neighbor list leads to optimal memory efficiency when combined with proper particle reordering schemes. We also propose an in-situ generation scheme for Gaussian random numbers that has a better performance without losing quality. In addition, details will be given on how to design custom transcendental functions that fit specifically to our DPD functional form. The code is scalable and can run on over a thousand nodes on the Titan supercomputer. Demonstration of large-scale DPD simulations on vesicle assembly and red blood cell suspension hydrodynamics using our code will be given.  Back
 
Keywords:
Molecular Dynamics, Numerical Algorithms & Libraries, Computational Fluid Dynamics, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4518
Streaming:
Download:
 
Virtual Screening of One Billion Compound Libraries Using Novel GPU-Accelerated Cheminformatics Approaches
Olexandr Isayev (University of North Carolina at Chapel Hill)
Recent years have seen an unprecedented growth of chemical databases incorporating tens of millions of available or up to 170 billion of synthetically feasible chemical compounds. They offer unprecedented opportunities for discovering novel molecules ...Read More
Recent years have seen an unprecedented growth of chemical databases incorporating tens of millions of available or up to 170 billion of synthetically feasible chemical compounds. They offer unprecedented opportunities for discovering novel molecules with the desired therapeutical and safety profile. However, current cheminformatics technologies and software relying on conventional CPUs are not capable to handle, characterize, and virtually screen such "Big Data" chemical libraries. We present the first proof-of-concept study of GPU-accelerated cheminformatics software capable of calculating chemical descriptors for a billion molecules-large library. Furthermore, we demonstrate the ability of GPU-based virtual screening software to rapidly identify compounds with specific properties in extremely large virtual libraries. We posit that in the era of big data explosion in chemical genomics, GPU computing represents an effective and inexpensive architecture to develop and employ a new generation of cheminformatics methods and tools.  Back
 
Keywords:
Molecular Dynamics, Big Data Analytics, GTC Silicon Valley 2014 - ID S4561
Streaming:
Download:
 
BUDE: GPU-Accelerated Molecular Docking for Drug Discovery
Richard Sessions (University of Bristol)
The Bristol University Docking Engine (BUDE) is next-generation molecular docking software exploiting GPUs to deliver a step change in performance. Massive sampling of search space, coupled with a novel method of estimating the free energy of binding ...Read More
The Bristol University Docking Engine (BUDE) is next-generation molecular docking software exploiting GPUs to deliver a step change in performance. Massive sampling of search space, coupled with a novel method of estimating the free energy of binding between the receptor and ligand (the docking partners), enables novel science. BUDE and a medium sized GPU-enabled supercomputer can be used to perform (1) virtual-screening-by-docking of 10 million drug-like molecules to a protein for drug discovery in a few days; (2) scanning of the surface of a protein with hundreds of drug-like molecules to locate binding sites; (3) protein-protein docking in real space for predicting important protein interactions involved in cellular signaling. In recent optimization work with BUDE, we have achieved a sustained 46% theoretical peak FLOPs on an NVIDIA GTX680.   Back
 
Keywords:
Molecular Dynamics, Bioinformatics & Genomics, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4604
Streaming:
Download:
 
GPU Optimized Allosteric Communication Network Analyses of Molecular Dynamic Simulations
Cody Stevens (Wake Forest University)
Biomolecular folding is a vital biological process and many diseases and disorders can be attributed to the inability for biomolecules to fold correctly and interact with one another. For our research, we analyzed the protein-RNA complex, MetRS:tRNA( ...Read More
Biomolecular folding is a vital biological process and many diseases and disorders can be attributed to the inability for biomolecules to fold correctly and interact with one another. For our research, we analyzed the protein-RNA complex, MetRS:tRNA(fMet) (547 residues and 76 nucleotides), using GPU-optimized graph analysis in order to find a correlation between allosteric protein signaling and graph pathways. These graph analyses were compared to in vitro mutation experiments in order to determine whether a correlation existed between these two metrics. By analyzing this correlation we hope to find a strong predictor for residue priority for in vitro mutation experiments.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2014 - ID P4246
Download:
 
AutoDock - Multiple GPUs Implementation
Dat Ho (Versalogies Ltd.)
AutoDock is open source, freely distributed, and steadily further developed, until today. However, with its traditional serial programming model, AutoDock cannot utilize the parallel computing power of multi/many cores hardware models nowadays. This ...Read More
AutoDock is open source, freely distributed, and steadily further developed, until today. However, with its traditional serial programming model, AutoDock cannot utilize the parallel computing power of multi/many cores hardware models nowadays. This leads to the limitation in performance of AutoDock even when it runs on powerful workstation or super-computer. This research shows an excellent result of parallelizing AutoDock with CUDA: spending little effort to CUDA-fy 1 small part of AutoDock and run it on multiple GPUs to achieve 13x - 43.5x speedup comparing to running on 1 CPU.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2014 - ID P4116
Download:
 
GPU-Based Atomistic Simulations on Spatio-Temporal Experimental Scales
Jeffrey Kelling (Technische Universitat Chemnitz)
The Kinetic Metropolis Lattice Monte-Carlo (KMC) method is a means of performing atomistic simulations of self-organization processes in solids at by far larger scales than those accessible via Molecular Dynamics. Employing a cellular automaton appro ...Read More
The Kinetic Metropolis Lattice Monte-Carlo (KMC) method is a means of performing atomistic simulations of self-organization processes in solids at by far larger scales than those accessible via Molecular Dynamics. Employing a cellular automaton approach allows incorporation of many body interactions and external driving forces. Here, we present an efficient KMC implementation on single and multiple GPUs, which allows us to study phase separation and nanostructure-evolution at spatio-temporal experimental scales. The KMC implementation has been used to develop with industrial partners a new Si-based nanocomposite for next-generation thin-film solar cells.  Back
 
Keywords:
Molecular Dynamics, GTC Silicon Valley 2014 - ID P4154
Download:
 
Optimizing CoMD: A Molecular Dynamics Proxy Application Study
Nikolay Sakharnykh (NVIDIA), Jamal Mohd-Yusof (LANL)
Learn about various methods and trade-offs in the distributed GPU implementation of molecular dynamics proxy application that achieves more than 90% weak scaling efficiency on 512 GPU nodes. CoMD represents a reference implementation of classica ...Read More

Learn about various methods and trade-offs in the distributed GPU implementation of molecular dynamics proxy application that achieves more than 90% weak scaling efficiency on 512 GPU nodes. CoMD represents a reference implementation of classical molecular dynamics algorithms and workloads. It is created and maintained by The Exascale Co-Design Center for Materials in Extreme Environments (ExMatEx) and is part of the R&D100 Award-winning Mantevo 1.0 software suite. In this talk we will discuss the main techniques and methods that are involved in GPU implementation of CoMD, including (1) cell-based and neighbor list approaches for neighbor particles search, (2) different thread-mapping strategies and memory layouts. An efficient distributed implementation will be covered in detail. Interior/boundary cells separation is used to allow efficient asynchronous processing and concurrent execution of kernels, memory copies and MPI transfers.

  Back
 
Keywords:
Molecular Dynamics, Computational Physics, GTC Silicon Valley 2014 - ID S4465
Streaming:
Download:
 
Heterogeneous CPU+GPU Molecular Dynamics engine in CHARMM with Biofuels Applications
Antti-Pekka Hynninen (NREL), Michael Crowley (NREL)
This is a first snapshot of the heterogeneous CPU+GPU Molecular Dynamics (MD) in CHARMM and its performance and the accuracy. GPU is used only for the direct part of forces; CPU computes all other contributions (reciprocal, bonded, SHAKE, etc.). ...Read More

This is a first snapshot of the heterogeneous CPU+GPU Molecular Dynamics (MD) in CHARMM and its performance and the accuracy. GPU is used only for the direct part of forces; CPU computes all other contributions (reciprocal, bonded, SHAKE, etc.). The GPU code was implemented natively in CHARMM using CUDA C. The MD engine is built around the DOMDEC domain decomposition code and therefore naturally enables MD simulations on multiple CPU+GPU nodes. We will present discoveries that used features implemented in DOMDEC_GPU, showing the current usefulness of the code and GPUs for biomolecular simulation, advanced sampling techniques, and for enabling DOE/NREL efforts toward affordable consumer biofuels.

  Back
 
Keywords:
Molecular Dynamics, GTC Webinars 2014 - ID GTCE103
Streaming:
Download:
Quantum Chemistry
Presentation
Media
Virtual Molecular Modelling Kits: Playing Games with Quantum Chemistry
Nathan Luehr (Stanford University)
We discuss the impact of GPU-based quantum chemistry calculations for small molecules. Based on a specially optimized version of TeraChem, we demonstrate real-time molecular dynamics for systems up to a few dozen atoms. Harnessing this performance, w ...Read More
We discuss the impact of GPU-based quantum chemistry calculations for small molecules. Based on a specially optimized version of TeraChem, we demonstrate real-time molecular dynamics for systems up to a few dozen atoms. Harnessing this performance, we describe the development of interactive interfaces to virtual quantum chemistry models. Such interfaces make possible a new paradigm for chemical education and research.  Back
 
Keywords:
Quantum Chemistry, Combined Simulation & Real-Time Visualization, Molecular Dynamics, GTC Silicon Valley 2014 - ID S4427
Streaming:
Download:
Rendering and Ray Tracing
Presentation
Media
Petascale Molecular Ray Tracing: Accelerating VMD/Tachyon with OptiX
John Stone (University of Illinois)
We describe the adaptation of VMD, a popular molecular visualization and analysis tool, to exploit the Tesla K20X GPU for acceleration of large scale molecular visualization runs on Cray XK7 petascale supercomputers such as Blue Waters and Titan. We ...Read More
We describe the adaptation of VMD, a popular molecular visualization and analysis tool, to exploit the Tesla K20X GPU for acceleration of large scale molecular visualization runs on Cray XK7 petascale supercomputers such as Blue Waters and Titan. We will describe ray tracing performance benefits and memory efficiency optimizations achieved through the use of custom geometric primitives and triangle mesh formats, and relate our experiences adapting the Tachyon CPU-based ray tracing engine used by VMD, to NVIDIA's OptiX GPU ray tracing framework. We will present performance data for large visualization runs on the Cray XK7, discuss our approach to integrating OptiX into VMD, and describe avenues for further improvement.  Back
 
Keywords:
Rendering and Ray Tracing, Molecular Dynamics, Scientific Visualization, HPC and Supercomputing, GTC Silicon Valley 2014 - ID S4400
Streaming:
Download:
Visual Effects & Simulation
Presentation
Media
Modeling Fracture on the GPU with Peridynamics
Joshua Levine (School of Computing, Visual Computing Division, Clemson University)
The modeling of shapes that fracture is a particularly challenging area for computer graphics simulation, typically Involving computationally expensive techniques based on classical continuum mechanics. Recently, a new theory of fracture, called per ...Read More
The modeling of shapes that fracture is a particularly challenging area for computer graphics simulation, typically Involving computationally expensive techniques based on classical continuum mechanics. Recently, a new theory of fracture, called peridynamics, has been introduced, and it offers a numerical method that is particularly suited for efficient solutions on the GPU. Peridynamics is of growing interest to the scientific community, but it has not yet been leveraged by computer graphics, in part because of difficulties in creating realistic renderings of the objects that fracture. We discuss our implementation of the peridynamic formulation in CUDA as well as experimentation of fracturing objects performed on NVIDIA Tesla K20s. Furthermore, we describe an embarrassingly parallel technique for rendering the resulting particle systems.  Back
 
Keywords:
Visual Effects & Simulation, Molecular Dynamics, Rendering and Ray Tracing, GTC Silicon Valley 2014 - ID S4432
Streaming: