high performance computing on graphics processing units: hgpu.org

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Capturing the Memory Topology of GPUs

Dominik Größler

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce 840 M, nVidia GeForce RTX 2080 Ti, nVidia Quadro P 6000, Package, Performance, PTX, Tesla K20, Tesla V100, Thesis

November 13, 2022 by hgpu

iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud

Fei Xu, Jianian Xu, Jiabin Chen, Li Chen, Ruitao Shang, Zhi Zhou, Fangming Liu

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Tags: Cloud, Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla V100

November 13, 2022 by hgpu

pyGSL: A Graph Structure Learning Toolkit

Max Wasserman, Gonzalo Mateos

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Tags: Computer science, Machine learning, Package, PyTorch, Signal processing

November 13, 2022 by hgpu

An Open-source FPGA Library for Data Sorting

Ryohei Kobayashi, Kento Miura, Norihisa Fujita, Taisuke Boku, Toshiyuki Amagasa

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Tags: Algorithms, Computer science, FPGA, OpenCL, Package, Sorting

November 6, 2022 by hgpu

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, Materials Science, Neural networks, Package, Python

November 6, 2022 by hgpu

A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

Erik Tedhamre

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, OpenCL, OpenMP, Package, Performance

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

torchode: A Parallel ODE Solver for PyTorch

Marten Lienen, Stephan Günnemann

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Tags: Computer science, Deep learning, Numerical Analysis, nVidia, nVidia GeForce GTX 1080 Ti, ODEs, Ordinary differential equations, Package, PyTorch

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

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

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

See all packages

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high performance computing on graphics processing units: hgpu.org

Capturing the Memory Topology of GPUs

pyGSL: A Graph Structure Learning Toolkit

An Open-source FPGA Library for Data Sorting

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

Providing performance portable numerics for Intel GPUs

torchode: A Parallel ODE Solver for PyTorch

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

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

Recent source codes

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

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