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GTC ON-DEMAND

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Abstract:
Learn how we used NVIDIA's Nsight tool suite to help focus the development effort and optimize NAMD, which is being rewritten to vastly increase its utilization of GPUs. We'll explain how sophisticated tools like NVIDIA's Nsight Systems and Nsight Compute help determine if an application is using compute resources efficiently and whether your GPUs are starving for work or completely overwhelmed. We'll discuss how the NAMD development team at the University of Illinois at Urbana-Champaign is using Nsight tools to solve real-life performance bugs and bottlenecks, such as streamlining host-to-GPU transfers and optimizing NAMD kernels. We'll also cover how we used a new direct data access API to develop a custom tool that parses Nsight Systems data to quickly find and debug performance outliers.
Learn how we used NVIDIA's Nsight tool suite to help focus the development effort and optimize NAMD, which is being rewritten to vastly increase its utilization of GPUs. We'll explain how sophisticated tools like NVIDIA's Nsight Systems and Nsight Compute help determine if an application is using compute resources efficiently and whether your GPUs are starving for work or completely overwhelmed. We'll discuss how the NAMD development team at the University of Illinois at Urbana-Champaign is using Nsight tools to solve real-life performance bugs and bottlenecks, such as streamlining host-to-GPU transfers and optimizing NAMD kernels. We'll also cover how we used a new direct data access API to develop a custom tool that parses Nsight Systems data to quickly find and debug performance outliers.  Back
 
Topics:
Tools & Libraries, Performance Optimization, Computational Biology & Chemistry
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9503
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Abstract:
In 2007, NAMD was the first full-featured production molecular dynamics software to use CUDA for accelerating its costliest computations. We'll describe our latest efforts, techniques, and results in our quest to optimize NAMD to make best use of the tremendous computational capabilities of state-of-the-art Volta GPUs, particularly in new dense node configurations such as the NVIDIA DGX and ORNL Summit systems that feature NVLink-connected GPUs. In existence now for over 20 years, NAMD is a sophisticated parallel molecular dynamics program. NAMD development has emphasized parallel scalability to support large-size and long-timescale biomolecular simulations running on petascale supercomputers. As GPU technology has evolved, NAMD has benefited from moving greater amounts of work to the GPU. NVIDIA's release of Volta has now shifted the balance almost entirely to the GPU, with the small remaining CPU calculations often posing bottlenecks to NAMD's performance. Attendees will learn optimization strategies and pitfalls for achieving higher performance as Amdahl's Law poses an ever increasing challenge for mature GPU-accelerated codes like NAMD.
In 2007, NAMD was the first full-featured production molecular dynamics software to use CUDA for accelerating its costliest computations. We'll describe our latest efforts, techniques, and results in our quest to optimize NAMD to make best use of the tremendous computational capabilities of state-of-the-art Volta GPUs, particularly in new dense node configurations such as the NVIDIA DGX and ORNL Summit systems that feature NVLink-connected GPUs. In existence now for over 20 years, NAMD is a sophisticated parallel molecular dynamics program. NAMD development has emphasized parallel scalability to support large-size and long-timescale biomolecular simulations running on petascale supercomputers. As GPU technology has evolved, NAMD has benefited from moving greater amounts of work to the GPU. NVIDIA's release of Volta has now shifted the balance almost entirely to the GPU, with the small remaining CPU calculations often posing bottlenecks to NAMD's performance. Attendees will learn optimization strategies and pitfalls for achieving higher performance as Amdahl's Law poses an ever increasing challenge for mature GPU-accelerated codes like NAMD.  Back
 
Topics:
Computational Biology & Chemistry, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8727
Streaming:
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