GPU

GPA: A GPU Performance Advisor Based on Instruction Sampling
Presented our work on GPU performance advisor at CGO21
Mar 1, 2021 9:34 PM — 9:34 PM Virtual
Slides
GPA: A GPU Performance Advisor Based on Instruction Sampling
Developing efficient GPU kernels can be difficult because of the complexity of GPU architectures and programming models. Existing …
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Measurement and Analysis of GPU-Accelerated OpenCL Computations on Intel GPUs
Graphics Processing Units (GPUs) have become a key technology for accelerating node performance in supercomputers, including the US …
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Outcomes of OpenMP Hackathon: OpenMP Application Experiences with the Offloading Model
This paper reports on experiences gained and practices adopted when using the latest features of OpenMP to port a variety of HPC …
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GVProf: A Value Profiler for GPU-Based Clusters
Presented a talk about our value profiling tool for GPUs
Nov 19, 2020 9:53 PM — 9:53 PM Virtual
Slides
Tools for Top-down Performance Analysis of GPU-Accelerated Applications
Presented the beta version of our comprehensive GPU profiling tool at ICS20
Jul 1, 2020 9:41 PM — 9:41 PM Virtual
Project Slides
A Tool for Top-down Performance Analysis of GPU-accelerated Applications
Presented a poster and a short talk about HPCToolkit’s GPU support
Apr 24, 2020 9:50 PM — 9:50 PM San Diego, CA, USA
Project Poster Slides
A Tool for Top-down Performance Analysis of GPU-Accelerated Applications
To support performance measurement and analysis of GPU-accelerated applications, we extended the HPCToolkit performance tools with …
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GVPROF: A Value Profiler for GPU-Based Clusters
GPGPUs are widely used in high-performance computing systems to accelerate scientific and machine learning workloads. Developing …
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Tools for Top-down Performance Analysis of GPU-Accelerated Applications
This paper describes extensions to Rice University’s HPCToolkit performance tools to support measurement and analysis of …
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