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Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Shaohuai Shi, Qiang Wang, Xiaowen Chu

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Package, Sparse matrix, Tesla P100

June 7, 2020 by hgpu

Evaluating the performance of HPC-style SYCL applications

Tom Deakin, Simon McIntosh-Smith

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Tags: Benchmarking, Computer science, Heterogeneous systems, OpenCL, OpenMP, Package, Performance, SYCL

May 31, 2020 by hgpu

SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing

Sohan Lal, Aksel Alpay, Philip Salzmann, Biagio Cosenza, Nicolai Stawinoga, Peter Thoman, Thomas Fahringer, Vincent Heuveline

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Tags: Benchmarking, Computer science, FPGA, Heterogeneous systems, Package, Performance, SYCL

May 24, 2020 by hgpu

BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages

Abhishek Shivkumar, Jack Weston, Raphael Lenain, Emil Fristed

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Tags: Computer science, Deep learning, Machine learning, Medicine, NLP, Package, Python

May 24, 2020 by hgpu

Deep Learning with GO

Derek L. Stinson

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Tags: Computer science, CUDA, Deep learning, Go, nVidia, nVidia GeForce GTX 1080 Ti, Package, Thesis

May 17, 2020 by hgpu

Importance of Data Loading Pipeline in Training Deep Neural Networks

Mahdi Zolnouri, Xinlin Li, Vahid Partovi Nia

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Tesla V100

May 10, 2020 by hgpu

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Gleison Souza Diniz Mendonça, Chunhua Liao, Fernando Magno Quintão Pereira

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Tags: Benchmarking, Code generation, Computer science, OpenMP, Package

May 3, 2020 by hgpu

Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite

Marius Meyer, Tobias Kenter, Christian Plessl

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Tags: Benchmarking, Computer science, FPGA, HLS, OpenCL, Package

April 26, 2020 by hgpu

GEVO: GPU Code Optimization using Evolutionary Computation

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, Package, PTX, Tesla P100

April 26, 2020 by hgpu

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

Tsung-Wei Huang, Dian-Lun Lin, Yibo Lin, Chun-Xun Lin

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, Package, Performance

April 26, 2020 by hgpu

OpenCL-Darknet: implementation and optimization of OpenCL-based deep learning object detection framework

Yongbon Koo, Sunghoon Kim, Young-guk Ha

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Tags: AMD Radeon R7, Computer science, CUDA, Deep learning, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

April 19, 2020 by hgpu

FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System

Size Zheng, Yun Liang, Shuo Wang, Renze Chen, Kaiwen Sheng

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Tags: Algorithms, Computer science, CUDA, FPGA, Heterogeneous systems, Machine learning, nVidia, OpenCL, Package, Tesla V100

April 19, 2020 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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high performance computing on graphics processing units: hgpu.org

Packages

Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Evaluating the performance of HPC-style SYCL applications

SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing

BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages

Deep Learning with GO

Importance of Data Loading Pipeline in Training Deep Neural Networks

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite

GEVO: GPU Code Optimization using Evolutionary Computation

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

OpenCL-Darknet: implementation and optimization of OpenCL-based deep learning object detection framework

FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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