high performance computing on graphics processing units: hgpu.org

Applications

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QGTC: Accelerating Quantized GNN via GPU Tensor Core

Yuke Wang, Boyuan Feng, Yufei Ding

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce RTX 3090, TPU

November 21, 2021 by hgpu

FLOWER: A Comprehensive Dataflow Compiler for High-Level Synthesis

Puya Amiri, Arsene Perard-Gayot, Richard Membarth, Philipp Slusallek, Roland Leißa, Sebastian Hack

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Tags: Computer science, Computer vision, FPGA, HLS, Image processing, OpenCL

November 21, 2021 by hgpu

Accelerating JPEG Decompression on GPUs

André Weißenberger, Bertil Schmidt

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Tags: Compression, CUDA, Image processing, nVidia, nVidia A100

November 21, 2021 by hgpu

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

Yutaro Akahoshi, Sinya Aoki, Tatsumi Aoyama, Issaku Kanamori, Kazuyuki Kanaya, Hideo Matsufuru, Yusuke Namekawa, Hidekatsu Nemura, Yusuke Taniguchi

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Tags: GPU cluster, HEP, High Energy Physics - Lattice, Numerical simulation, nVidia, OpenACC, Package, Physics, QCD, Tesla V100

November 14, 2021 by hgpu

Performance Optimisations for Heterogeneous Managed Runtime Systems

Michail Papadimitriou

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Tags: Computer science, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1650, OpenCL, Performance, Thesis

November 14, 2021 by hgpu

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Yuhang Li, Mingzhu Shen, Jian Ma, Yan Ren, Mingxin Zhao, Qi Zhang, Ruihao Gong, Fengwei Yu, Junjie Yan

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Tags: Algorithms, ASIC, Benchmarking, Computer science, Deep learning, DSP, Package

November 14, 2021 by hgpu

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Zane Fink, Simeng Liu, Jaemin Choi, Matthias Diener, Laxmikant V. Kale

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Tags: Benchmarking, Computer science, CUDA, Distributed computing, HPC, Machine learning, MPI, nVidia, Package, Performance, Python, Tesla V100

November 14, 2021 by hgpu

Collage: Automated Integration of Deep Learning Backends

Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 2070, Tesla V100

November 7, 2021 by hgpu

iGUARD: In-GPU Advanced Race Detection

Aditya K Kamath, Arkaprava Basu

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Tags: Computer science, CUDA, nVidia, nVidia Titan RTX, Package, Performance

November 7, 2021 by hgpu

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Marco Hartmann, Lukas Weber, Johannes Wirth, Lukas Sommer, Andreas Koch

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Tags: Computer science, FPGA, Machine learning, Performance

November 7, 2021 by hgpu

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

Jan Hückelheim, Laurent Hascoët

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Tags: Code generation, Computer science, Machine learning, OpenMP, Package, Performance

November 7, 2021 by hgpu

Kernel Tuner

Bayesian Optimization for auto-tuning GPU kernels

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice

HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments

BAT: A standardized benchmark suite for auto-tuners

BAT: A Benchmark suite for AutoTuners

The Darmstadt Automotive Parallel HeterogeNEous (DAPHNE) Benchmark-Suite

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

iGUARD: In-GPU Advanced Race Detection

TaPaSCo: The Task Parallel System Composer

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Tapenade Automatic Differentiation Engine

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

QGTC: Accelerating Quantized GNN via GPU Tensor Core

FLOWER: A Comprehensive Dataflow Compiler for High-Level Synthesis

Accelerating JPEG Decompression on GPUs

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

Performance Optimisations for Heterogeneous Managed Runtime Systems

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Collage: Automated Integration of Deep Learning Backends

iGUARD: In-GPU Advanced Race Detection

Optimizing a Hardware Network Stack to Realize an In-Network ML Inference Application

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

Recent source codes

Kernel Tuner

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice

BAT: A standardized benchmark suite for auto-tuners

The Darmstadt Automotive Parallel HeterogeNEous (DAPHNE) Benchmark-Suite

General purpose lattice QCD code set Bridge++ 2.0 for high performance computing

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

iGUARD: In-GPU Advanced Race Detection

TaPaSCo: The Task Parallel System Composer

Tapenade Automatic Differentiation Engine

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