GPU

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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Optimizing GPU-accelerated Applications with HPCToolkit
Presented the prototype of HPCToolkit’s GPU support at PETASCALE'19
Jul 29, 2019 9:56 PM — 9:56 PM Lake Tahoe, California
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A Tool for Performance Analysis of GPU-accelerated Applications
Presented a talk about our profiling tool at CGO'19
Mar 18, 2019 11:10 PM — 11:10 PM Washington DC, USA
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A Tool for Performance Analysis of GPU-Accelerated Applications
Architectures for High-Performance Computing (HPC) now commonly employ accelerators such as Graphics Processing Units (GPUs). …
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A Performance Analysis Framework for Exploiting GPU Microarchitectural Capability
Presented our work on static performance analysis for GPUs at ICS17
Jul 20, 2017 9:36 PM — 9:36 PM Chicago, IL, USA
Slides
Deep Learning on Modern Architectures
Discussed how state-of-the-art deep learning libraries optimize computations by utilizing architectural features.
Apr 1, 2017 10:00 PM — 10:00 PM Institute of Computing Technology, Chinese Academy of Sciences
Slides
A Performance Analysis Framework for Exploiting GPU Microarchitectural Capability
GPUs are widely used in accelerating deep neural networks (DNNs) for their high bandwidth and parallelism. But tuning the performance …
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Understanding the GPU Microarchitecture to Achieve Bare-Metal Performance Tuning
In this paper, we present a methodology to understand GPU microarchitectural features and improve performance for compute-intensive …
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