high performance computing on graphics processing units: hgpu.org

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Fast matrix multiplies using graphics hardware

E. Scott Larsen, David Mcallister

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Tags: Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 3, OpenGL

November 24, 2010 by hgpu

Power Efficient Large Matrices Multiplication by Load Scheduling on Multi-core and GPU Platform with CUDA

DaQi Ren, Reiji Suda

Tags: Computer science, CUDA, Energy-efficient computing, Matrix multiplication, nVidia

November 8, 2010 by hgpu

Solving Path Problems on the GPU

Aydin Buluc, John R. Gilbert, Ceren Budak

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 8800 Ultra, Package, Path problems

November 5, 2010 by hgpu

Faster matrix-vector multiplication on GeForce 8800GTX

N. Fujimoto

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTX

November 5, 2010 by hgpu

Quantum Monte Carlo on graphical processing units

A. Anderson, W. Goddard, P. Schroder

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Tags: Computational Physics, Floating point error, Matrix multiplication, Monte Carlo simulation, nVidia GeForce 7800 GTX, Physics

November 3, 2010 by hgpu

Improving Performance of Matrix Multiplication and FFT on GPU

Xiang Cui, Yifeng Chen, Hong Mei

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Tags: Computer science, CUDA, FFT, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280

November 2, 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

Fast matrix multiplies using graphics hardware

Power Efficient Large Matrices Multiplication by Load Scheduling on Multi-core and GPU Platform with CUDA

Solving Path Problems on the GPU

Faster matrix-vector multiplication on GeForce 8800GTX

Quantum Monte Carlo on graphical processing units

Improving Performance of Matrix Multiplication and FFT on GPU

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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