high performance computing on graphics processing units: hgpu.org

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Parallel Position Weight Matrices Algorithms

Mathieu Giraud, Jean-Stephane Varre

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Tags: Biology, Computer science, CUDA, nVidia, nVidia GeForce 8800, nVidia GeForce GTX 280, Package

November 22, 2010 by hgpu

GPGPU computation and visualization of three-dimensional cellular automata

Stephane Gobron, Arzu Coltekin, Herve Bonafos and Daniel Thalmann

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Tags: Cellular automata, Computer science, Medicine, nVidia, nVidia GeForce 8800 GTX, OpenGL, Package, Visualization

November 20, 2010 by hgpu

A GPGPU compiler for memory optimization and parallelism management

Yi Yang, Ping Xiang, Jingfei Kong, Huiyang Zhou

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Tags: Computer science, CUBLAS, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Package

November 18, 2010 by hgpu

Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

Stanimire Tomov, Rajib Nath, Jack Dongarra

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Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Package

November 17, 2010 by hgpu

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Brice Boyer, Jean-Guillaume Dumas, Pascal Giorgi

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Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GTX 280, OpenMP, Package, Sparse matrix, Symbolic Computation

November 11, 2010 by hgpu

Rank k Cholesky Up/Down-dating on the GPU: gpucholmodV0.2

Christian Walder

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, Tesla C2050

November 9, 2010 by hgpu

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Imran S. Haque, Vijay S. Pande

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9500 GT, Package, Tesla C870

November 9, 2010 by hgpu

HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

Danny van Dyk, Markus Geveler, Sven Mallach, Dirk Ribbrock, Dominik Goeddeke, Carsten Gutwenger

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Tags: Cell processor, Computer science, CUDA, Mathematical Software, Mixed precision, nVidia, nVidia GeForce 8800 GTX, Package

November 9, 2010 by hgpu

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Samer Al-Kiswany, Abdullah Gharaibeh, Elizeu Santos-Neto, George Yuan, Matei Ripeanu

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 9800 GTX, Package, Storage system

November 6, 2010 by hgpu

RenderAnts: Interactive REYES Rendering on GPUs

Kun Zhou, Qiming Hou, Zhong Ren, Minmin Gong, Xin Sun, Baining Guo

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Tags: Computer science, Image generation, nVidia, nVidia GeForce GTX 280, Package, Raytracing, Rendering, Shaders

November 5, 2010 by hgpu

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Anthony Danalis,Gabriel Marin,Collin McCurdy,Jeremy S. Meredith,Philip C. Roth,Kyle Spafford,Vinod Tipparaju,Jeffrey S. Vetter

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Tags: ATI, ATI Radeon HD 5770, ATI Radeon HD 5870, ATI Stream, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, OpenCL, Package, Performance, Tesla C1060

November 5, 2010 by hgpu

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

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel Position Weight Matrices Algorithms

GPGPU computation and visualization of three-dimensional cellular automata

A GPGPU compiler for memory optimization and parallelism management

Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Rank k Cholesky Up/Down-dating on the GPU: gpucholmodV0.2

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

RenderAnts: Interactive REYES Rendering on GPUs

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Recent source codes

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

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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