high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Optimizing MapReduce for GPUs with effective shared memory usage

Linchuan Chen, Gagan Agrawal

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Tags: Computer science, Heterogeneous systems, MapReduce, Memory, nVidia, nVidia Quadro FX 5800, Performance

July 16, 2012 by hgpu

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

Abdullah Gharaibeh, Lauro Beltrao Costa, Elizeu Santos-Neto, Matei Ripeanu

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Tags: Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, Optimization, Performance, Programming Languages, Programming techniques, Tesla C2050

July 16, 2012 by hgpu

ab-Stream: A Framework for programming Many-core

Xinbiao Gan, Zhiying Wang, Li Shen, Qi Zhu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

July 15, 2012 by hgpu

A Performance Model for Memory Bandwidth Constrained Applications on Graphics Engines

Lin Ma, Roger D. Chamberlain

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Tags: Biology, BLAST, Computational biology, CUDA, Hashing, nVidia, nVidia GeForce GTX 480, Performance

July 15, 2012 by hgpu

Towards Parallel Programming Models for Predictability

Bjorn Lisper

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance

July 12, 2012 by hgpu

A Generic Library for Stencil Computations

Mauro Bianco, Ugo Varetto

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Mathematical Software, MPI, nVidia, PC cluster, Performance, Tesla M2090

July 10, 2012 by hgpu

Performance models for CUDA streams on NVIDIA GeForce series

Juan Gomez-Luna, Jose Maria Gonzalez-Linares, Jose Ignacio Benavides, Nicolas Guil

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Performance

July 9, 2012 by hgpu

Parallel Memory Defragmentation on a GPU

Ronald Veldema, Michael Philippsen

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Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 560 Ti, Performance, Storage system

July 6, 2012 by hgpu

GPUs as an Opportunity for Offloading Garbage Collection

Martin Maas, Philip Reames, Jeffrey Morlan, Krste Asanovic, Anthony D. Joseph, John Kubiatowicz

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Tags: Algorithms, APU, Computer science, Memory, OpenCL, Performance

June 29, 2012 by hgpu

Software Performance Analysis with Parallel Programming Approaches

Suneeta H. Angadi, G. T. Raju, Abhishek B

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Tags: Computer science, Matrix multiplication, OpenCL, OpenMP, Optimization, Performance

June 27, 2012 by hgpu

Hierarchical overlapped tiling

Xing Zhou, Jean-Pierre Giacalone, Maria Jesus Garzaran, Robert H Kuhn, Yang Ni, David Padua

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Tags: Compilers, Computer science, OpenCL, Performance

June 23, 2012 by hgpu

Evaluating the impact of reordering unstructured meshes on the performance of finite volume GPU solvers

Marc de la Asuncion, Jose M. Mantas, Manuel J. Castro

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Tags: Computer science, CUDA, Finite volume method, nVidia, nVidia GeForce GTX 580, Performance

June 21, 2012 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

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high performance computing on graphics processing units: hgpu.org

Optimizing MapReduce for GPUs with effective shared memory usage

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

ab-Stream: A Framework for programming Many-core

A Performance Model for Memory Bandwidth Constrained Applications on Graphics Engines

Towards Parallel Programming Models for Predictability

A Generic Library for Stencil Computations

Performance models for CUDA streams on NVIDIA GeForce series

Parallel Memory Defragmentation on a GPU

GPUs as an Opportunity for Offloading Garbage Collection

Software Performance Analysis with Parallel Programming Approaches

Hierarchical overlapped tiling

Evaluating the impact of reordering unstructured meshes on the performance of finite volume GPU solvers

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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