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CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUDA, Data parallelism, FFT, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

October 2, 2011 by hgpu

Correctly Treating Synchronizations in Compiling Fine-Grained SPMD-Threaded Programs for CPU

Ziyu Guo, Eddy Z. Zhang, Xipeng Shen

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia

October 1, 2011 by hgpu

Optimizing a Semantic Comparator using CUDA-enabled Graphics Hardware

Aalap Tripathy, Suneil Mohan, Rabi Mahapatra

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Tags: Bloom filter, Computer science, CUDA, Green, Hashing, nVidia, Semantic indexing, Tesla C870

October 1, 2011 by hgpu

Customizable Domain-Specific Computing

Jason Cong, Glenn Reinman, Alex Bui, Vivek Sarkar

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Tags: Computer science, FPGA, nVidia, Performance, Programming techniques, Tesla C1060

October 1, 2011 by hgpu

CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications

Hiroyuki Takizawa, Kentaro Koyama, Katuto Sato, Kazuhiko Komatsu, Hiroaki Kobayashi

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, MPI, nVidia, OpenCL, Tesla C1060

October 1, 2011 by hgpu

A Comprehensive Performance Comparison of CUDA and OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 1, 2011 by hgpu

Accelerating Vector Calculations on GPU

Karol Grondzak, Penka Martincova, Ondrej Such

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tutorial

October 1, 2011 by hgpu

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Gregory Diamos, Sudnya Padalikar

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, Memory, nVidia, Performance, PTX, Tesla C1060

September 30, 2011 by hgpu

Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems

Mayank Daga

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Heterogeneous systems, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050, Thesis

September 30, 2011 by hgpu

Real-Time Handling of GPU Interrupts in LITMUSRT

Glenn A. Elliott, Chih-Hao Sun, and James H. Anderson

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Operating systems

September 30, 2011 by hgpu

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

Bo Wu, Eddy Z. Zhang, Xipeng Shen

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Tags: Algorithms, Benchmarking, CMP, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Tesla S1070

September 30, 2011 by hgpu

Stack-less SIMT reconvergence at low cost

Sylvain Collange

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Tags: ATI, Computer science, Hardware Architecture, Memory, nVidia, Performance

September 30, 2011 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Correctly Treating Synchronizations in Compiling Fine-Grained SPMD-Threaded Programs for CPU

Optimizing a Semantic Comparator using CUDA-enabled Graphics Hardware

Customizable Domain-Specific Computing

CheCL: Transparent Checkpointing and Process Migration of OpenCL Applications

A Comprehensive Performance Comparison of CUDA and OpenCL

Accelerating Vector Calculations on GPU

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems

Real-Time Handling of GPU Interrupts in LITMUSRT

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

Stack-less SIMT reconvergence at low cost

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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