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GTC ON-DEMAND

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Abstract:
We'll explore the challenges of accelerating an adaptive Cartesian mesh CFD Solver, PARAS-3D, in existing CPUs and GPUs. The memory-bound nature of CFD codes is an obstacle to higher performance, and the opt-tree structure of adaptive Cartesian meshes adds the challenge of data parallelism. Cartesian mesh solvers have higher memory bandwidth requirements due to their larger and varying stencil. We'll detail how redesigning and implementing a legacy Cartesian mesh CFD solver and improving algorithms and data structures helped us achieve higher performance in CPUs. We'll also explain how we used a structure of array-based data layout and GPU features like Unified Memory and Multi Process Service to improve GPU performance over a CPU-only version.
We'll explore the challenges of accelerating an adaptive Cartesian mesh CFD Solver, PARAS-3D, in existing CPUs and GPUs. The memory-bound nature of CFD codes is an obstacle to higher performance, and the opt-tree structure of adaptive Cartesian meshes adds the challenge of data parallelism. Cartesian mesh solvers have higher memory bandwidth requirements due to their larger and varying stencil. We'll detail how redesigning and implementing a legacy Cartesian mesh CFD solver and improving algorithms and data structures helped us achieve higher performance in CPUs. We'll also explain how we used a structure of array-based data layout and GPU features like Unified Memory and Multi Process Service to improve GPU performance over a CPU-only version.  Back
 
Topics:
Computational Fluid Dynamics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9665
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Abstract:
We will demonstrate the features and capabilities of OpenACC for porting and optimizing the ParDOCK docking module of the Sanjeevini suite for computer aided drug discovery developed at the HPC and Supercomputing Facility for Bioinformatics and Computational Biology at the Indian Institute of Technology Delhi. We have used OpenACC to efficiently port the existing C++ programming model of ParDOCK software with minimal code modifications to run on latest NVIDIA P100 GPU card. These code modifications and tuning resulted in a six times average speedup of improvements in turnaround time. By implementing openACC, the code is now able to sample ten times more ligand conformations leading to an increase in accuracy. The ACC ported ParDOCK code is now able to predict a correct pose of a protein-ligand interaction from 96.8 percent times, compared to 94.3 percent earlier (for poses under 1 A) and 89.9 percent times compared to 86.7 percent earlier (for poses under 0.5 A).
We will demonstrate the features and capabilities of OpenACC for porting and optimizing the ParDOCK docking module of the Sanjeevini suite for computer aided drug discovery developed at the HPC and Supercomputing Facility for Bioinformatics and Computational Biology at the Indian Institute of Technology Delhi. We have used OpenACC to efficiently port the existing C++ programming model of ParDOCK software with minimal code modifications to run on latest NVIDIA P100 GPU card. These code modifications and tuning resulted in a six times average speedup of improvements in turnaround time. By implementing openACC, the code is now able to sample ten times more ligand conformations leading to an increase in accuracy. The ACC ported ParDOCK code is now able to predict a correct pose of a protein-ligand interaction from 96.8 percent times, compared to 94.3 percent earlier (for poses under 1 A) and 89.9 percent times compared to 86.7 percent earlier (for poses under 0.5 A).  Back
 
Topics:
Computational Biology & Chemistry, Performance Optimization, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8188
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Abstract:
This talk will introduce you to the extensions made in the Thrust Library to provide means and methodologies to facilitate the development of structured, ef?cient and portable parallel medical imaging applications with minimal loss in performance as compared to the hand optimized code. Thrust++ library adds 2D/3D data structures, imaging algorithms, and patterns optimized for usage in medical applications. We will demonstrate the result of our extensions to Thrust on Computed Tomography Reconstruction using cone beam reconstruction technique called Feldkamp algorithm. Our experimental results demonstrates that abstraction improves the productivity and not only ensures ease of use but also provides performance at par with native implementation
This talk will introduce you to the extensions made in the Thrust Library to provide means and methodologies to facilitate the development of structured, ef?cient and portable parallel medical imaging applications with minimal loss in performance as compared to the hand optimized code. Thrust++ library adds 2D/3D data structures, imaging algorithms, and patterns optimized for usage in medical applications. We will demonstrate the result of our extensions to Thrust on Computed Tomography Reconstruction using cone beam reconstruction technique called Feldkamp algorithm. Our experimental results demonstrates that abstraction improves the productivity and not only ensures ease of use but also provides performance at par with native implementation  Back
 
Topics:
Tools & Libraries, Medical Imaging & Radiology
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5338
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