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Benchmarking GPU and TPU Performance with Graph Neural Networks

Xiangyang Ju, Yunsong Wang, Daniel Murnane, Nicholas Choma, Steven Farrell, Paolo Calafiura

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia A100, Pattern recognition, Tesla V100, TPU

October 30, 2022 by hgpu

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Taha Tekdoğan, Serkan Göktaş, Ayse Yilmazer-Metin

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Tags: Benchmarking, Computer science, CUDA, Machine learning, Neural networks, nVidia, Performance, Tesla V100

October 30, 2022 by hgpu

Providing performance portable numerics for Intel GPUs

Yu-Hsiang M. Tsai, Terry Cojean, Hartwig Anzt

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, OpenCL, Package, performance portability, Sparse, SYCL

October 30, 2022 by hgpu

A Ray Tracing Implementation Performance Comparison between the CPU and the GPU

Robin Nordmark, Tim Olsén

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Tags: 3D Graphics and Realism, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Raytracing, Rendering

October 23, 2022 by hgpu

Tausch: A halo exchange library for large heterogeneous computing systems using MPI, OpenCL, and CUDA

Lukas Spies, Amanda Bienz, David Moulton, Luke Olson, Andrew Reisner

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, OpenCL, Package, Tesla V100

October 23, 2022 by hgpu

Thwarting Piracy: Anti-debugging Using GPU-assisted Self-healing Codes

Adhokshaj Mishra, Manjesh Kumar Hanawal

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 960 M, Security

October 23, 2022 by hgpu

From Task-Based GPU Work Aggregation to Stellar Mergers: Turning Fine-Grained CPU Tasks into Portable GPU Kernels

Gregor Daiß, Patrick Diehl, Dominic Marcello, Alireza Kheirkhahan, Hartmut Kaiser, Dirk Pflüger

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Tags: AMD Radeon Instinct MI100, Astrophysics, ATI, CUDA, HIP, nVidia, nVidia A100, Package, performance portability, Physics

October 23, 2022 by hgpu

Distributed, combined CPU and GPU profiling within HPX using APEX

Patrick Diehl, Gregor Daiss, Kevin Huck, Dominic Marcello, Sagiv Shiber, Hartmut Kaiser, Juhan Frank, Geoffrey C. Clayton, Dirk Pflueger

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Tags: Astrophysics, Benchmarking, Computer science, CUDA, nVidia, Package, Tesla P100, Tesla V100

October 16, 2022 by hgpu

Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models

JooYoung Park, DoangJoo Synn, XinYu Piao, Jong-Kook Kim

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 3080 Ti, Performance, Prefetch

October 16, 2022 by hgpu

OpenMP Offloading in the Jetson Nano Platform

Ilias K. Kasmeridis, Vassilios V. Dimakopoulos

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia Jetson Nano, OpenMP, Package

October 16, 2022 by hgpu

Bottleneck Analysis of Dynamic Graph Neural Network Inference on CPU and GPU

Hanqiu Chen, Yahya Alhinai, Yihan Jiang, Eunjee Na, Cong Hao

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia RTX A6000, Package

October 16, 2022 by hgpu

Towards Performance Portable Programming for Distributed Heterogeneous Systems

Polykarpos Thomadakis, Nikos Chrisochoides

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, Performance, performance portability, Tesla V100

October 9, 2022 by hgpu

CATO: automatic source transformation to apply HPC frameworks with minimal user interaction

Compiler-assisted distribution of OpenMP code for improved scalability

ADIOS2.jl: a Julia interface to ADIOS2

Julia as a unifying end-to-end workflow language on the Frontier exascale system

Code generated HPC Kernels Using Llama-2-70b

Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation

Scope is all you need: Transforming LLMs for HPC Code

pocl - Portable Computing Language

PoCL-R: An Open Standard Based Offloading Layer for Heterogeneous Multi-Access Edge Computing with Server Side Scalability

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

openCLDispatcher

Novel insights on atomic synchronization for sort-based group-by on GPUs

CEED Benchmarks

Performant low-order matrix-free finite element kernels on GPU architectures

Sieve: Stratified GPU-Compute Workload Sampling

EngineCL: Usability and Performance in Heterogeneous Computing

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

See all packages

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high performance computing on graphics processing units: hgpu.org

Benchmarking GPU and TPU Performance with Graph Neural Networks

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Providing performance portable numerics for Intel GPUs

A Ray Tracing Implementation Performance Comparison between the CPU and the GPU

Tausch: A halo exchange library for large heterogeneous computing systems using MPI, OpenCL, and CUDA

Thwarting Piracy: Anti-debugging Using GPU-assisted Self-healing Codes

From Task-Based GPU Work Aggregation to Stellar Mergers: Turning Fine-Grained CPU Tasks into Portable GPU Kernels

Distributed, combined CPU and GPU profiling within HPX using APEX

Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models

OpenMP Offloading in the Jetson Nano Platform

Bottleneck Analysis of Dynamic Graph Neural Network Inference on CPU and GPU

Towards Performance Portable Programming for Distributed Heterogeneous Systems

Recent source codes

CATO: automatic source transformation to apply HPC frameworks with minimal user interaction

ADIOS2.jl: a Julia interface to ADIOS2

Code generated HPC Kernels Using Llama-2-70b

Scope is all you need: Transforming LLMs for HPC Code

pocl - Portable Computing Language

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

openCLDispatcher

CEED Benchmarks

Sieve: Stratified GPU-Compute Workload Sampling

EngineCL: Usability and Performance in Heterogeneous Computing

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