high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

Improving accuracy for matrix multiplications on GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Performance

March 22, 2011 by hgpu

A Fast GEMM Implementation On a Cypress GPU

Naohito Nakasato

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5870, ATI Stream, Computer science, Linear Algebra

March 18, 2011 by hgpu

Scientific Computation Through a GPU

Genna Cummins, Rob Adams, Theodore Newell

Tags: Computer science, CUDA, Linear Algebra, nVidia

March 18, 2011 by hgpu

FPGA vs. GPU for sparse matrix vector multiply

Yan Zhang, Yasser H. Shalabi, Rishabh Jain, Krishna K. Nagar, Jason D. Bakos

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Tags: Computer science, CUDA, FPGA, Linear Algebra, nVidia, nVidia GeForce GTX 260, Sparse matrix

March 18, 2011 by hgpu

A Quantitative Performance Analysis Model for GPU Architectures

Yao Zhang, John D. Owens

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Tags: Computer science, CUDA, Hardware Architecture, Linear Algebra, nVidia, nVidia GeForce GTX 285, Optimization

March 13, 2011 by hgpu

GEMM on a GPU

Jonathan Monette

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Poster

March 12, 2011 by hgpu

The GPU as a high performance computational resource

Tor Dokken, Trond R Hagen, Jon M Hjelmervik

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Tags: Computer science, Linear Algebra, Mathematical Software, Partial differential equations, PDEs, Review

March 11, 2011 by hgpu

Dense Matrix Algebra on the GPU

Adam Moravanszky

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Tags: ATI, ATI Radeon 9500 Pro, ATI Radeon 9700 Pro, Computer science, DirectX, Linear Algebra, Matrix multiplication

February 24, 2011 by hgpu

Accelerating the ANSYS Direct Sparse Solver with GPUs

Geraud P. Krawezik, Gene Poole

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Tags: Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, Sparse direct solvers, Tesla C1060

February 22, 2011 by hgpu

Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms

Hartwig Anzt, Bjorn Rocker, Vincent Heuveline

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Tags: Computer science, Energy-efficient computing, Linear Algebra, Mixed precision, nVidia, Tesla C1060, Tesla S1070

February 22, 2011 by hgpu

High Performance Relevance Vector Machine on GPUs

Depeng Yang, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL

February 19, 2011 by hgpu

Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs

JunKyu Lee, Junqing Sun, Gregory D. Peterson, Robert J. Harrison, Robert J. Hinde

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Tags: Computer science, Energy-efficient computing, FPGA, Linear Algebra, Mixed precision, nVidia, Performance, Tesla C1060

February 18, 2011 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

Improving accuracy for matrix multiplications on GPUs

A Fast GEMM Implementation On a Cypress GPU

Scientific Computation Through a GPU

FPGA vs. GPU for sparse matrix vector multiply

A Quantitative Performance Analysis Model for GPU Architectures

GEMM on a GPU

The GPU as a high performance computational resource

Dense Matrix Algebra on the GPU

Accelerating the ANSYS Direct Sparse Solver with GPUs

Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms

High Performance Relevance Vector Machine on GPUs

Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs

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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