high performance computing on graphics processing units: hgpu.org

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Performance assessment of CUDA and OpenACC in large scale combustion simulations

Guillermo Oyarzun, Daniel Mira, Guillaume Houzeaux

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Tags: CUDA, nVidia, OpenACC, Performance, Physics, Tesla V100

August 8, 2021 by hgpu

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

Daniel Gerzhoy

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Tags: Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

August 8, 2021 by hgpu

StreamBlocks: A compiler for heterogeneous dataflow computing

Endri Bezati, Mahyar Emami, Jörn Janneck, James Larus

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, OpenCL, Package, Performance

July 25, 2021 by hgpu

Optimisation and GPU code generation of Stencils for Futhark

Christian Charlie Virt, Jonathan Wraa-Hansen

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, nVidia GeForce RTX 2080 Ti, OpenCL, Performance, Thesis

July 18, 2021 by hgpu

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Dominik Ernst, Georg Hager, Markus Holzer, Matthias Knorr, Gerhard Wellein

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Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, Performance, Stencil computation, Tesla V100

July 11, 2021 by hgpu

kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos

Keichi Takahashi, Wassapon Watanakeesuntorn, Kohei Ichikawa, Joseph Park, Ryousei Takano, Jason Haga, George Sugihara, Gerald M. Pao

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Tags: Computer science, CUDA, HPC, nVidia, OpenCL, Package, Performance, performance portability

May 30, 2021 by hgpu

NPBench: A Benchmarking Suite for High-Performance NumPy

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

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Tags: Benchmarking, Computer science, CUDA, HPC, Linear Algebra, nVidia, Package, Performance, Python, Tesla V100

May 16, 2021 by hgpu

Winograd Algorithm for AdderNet

Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang

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Tags: Algorithms, CNN, Computer science, Deep learning, FPGA, Machine learning, Neural networks, Performance

May 16, 2021 by hgpu

Performance analysis and optimization of highly diverging algorithms on GPUs

Hendrik Schwanekamp

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Tags: CUDA, nVidia, nVidia A100, nVidia GeForce GTX 1080, Performance, Physics

May 2, 2021 by hgpu

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

Hamid Tabani, Fabio Mazzocchetti, Pedro Benedicte, Jaume Abella, Francisco J. Cazorla

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, Performance

April 25, 2021 by hgpu

Performance Monitoring of Multi-FPGA Systems

Arzhang Rafii

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Tags: Computer science, FPGA, Package, Performance, Thesis

April 11, 2021 by hgpu

Accelerating Deep Neural Networks implementation: A survey

Meriam Dhouibi, Ahmed Karim Ben Salem, Afef Saidi, Slim Ben Saoud

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Tags: ASIC, Computer science, Deep learning, FPGA, HLS, Neural networks, OpenCL, Optimization, Performance, survey

March 28, 2021 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

Performance assessment of CUDA and OpenACC in large scale combustion simulations

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

StreamBlocks: A compiler for heterogeneous dataflow computing

Optimisation and GPU code generation of Stencils for Futhark

Opening the Black Box: Performance Estimation during Code Generation for GPUs

kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos

NPBench: A Benchmarking Suite for High-Performance NumPy

Winograd Algorithm for AdderNet

Performance analysis and optimization of highly diverging algorithms on GPUs

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

Performance Monitoring of Multi-FPGA Systems

Accelerating Deep Neural Networks implementation: A survey

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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