high performance computing on graphics processing units: hgpu.org

Arvind K. Sujeeth, Tiark Rompf, Kevin J. Brown, HyoukJoong Lee, Hassan Chafi, Victoria Popic, Michael Wu, Aleksander Prokopec, Vojin Jovanovic, Martin Odersky, Kunle Olukotun

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Tags: Computer science, CUDA, MPI, nVidia, Package, Performance, Tesla C2050

May 31, 2013 by hgpu

Tiling optimizations for stencil computations

Xing Zhou

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Tags: Computer science, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Thesis

May 31, 2013 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Tesla C2050, Tesla C2070

May 30, 2013 by hgpu

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Joshua Penton

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Tags: ATI, ATI Radeon HD 6750 M, Computer science, FFT, Java, OpenCL, Package, Performance, Programming techniques

May 28, 2013 by hgpu

Performance Portability in Accelerated Parallel Kernels

John A. Stratton, Hee-Seok Kim, Thoman B. Jablin, Wen-Mei W. Hwu

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

May 27, 2013 by hgpu

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Konstantinos Menychtas, Kai Shen, Michael L. Scott

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 670, nVidia Quadro NVS 295, Performance

May 25, 2013 by hgpu

OpenCL Performance Evaluation on Modern Multi Core CPUs

Joo Hwan Lee, Kaushik Patel, Nimit Nigania, Hyojong Kim, Hyesoon Kim

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

May 25, 2013 by hgpu

GEMTC: GPU Enabled Many-Task Computing

Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Performance

May 25, 2013 by hgpu

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

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

A Reliable Throughput Gain on GPUs

Automating elimination of idle functions by run-time reconfiguration

Towards shared memory consistency models for GPUs

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Composition and Reuse with Compiled Domain-Specific Languages

Tiling optimizations for stencil computations

Performance Tradeoff Spectrum of Integer and Floating Point Applications

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Performance Portability in Accelerated Parallel Kernels

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

OpenCL Performance Evaluation on Modern Multi Core CPUs

GEMTC: GPU Enabled Many-Task Computing

Recent source codes

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

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

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