high performance computing on graphics processing units: hgpu.org

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An efficient GPU implementation of the revised simplex method

J. Bieling, P. Peschlow, P. Martini

Tags: Computer science, Programming techniques

April 20, 2011 by hgpu

Tutorial 3: Methodologies and Performance Impacts of General Purpose Computing on GPUs

Shinichi Yamagiwa

Tags: Computer science, Review, Tutorial

April 20, 2011 by hgpu

Design and implementation of software-managed caches for multicores with local memory

Sangmin Seo, Jaejin Lee, Zehra Sura

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Tags: Cell processor, Computer science, Memory model, OpenMP

April 20, 2011 by hgpu

Compressing Floating-Point Number Stream for Numerical Applications

Hisanobu Tomari, Mary Inaba, Kei Hiraki

Tags: Algorithms, Compression, Computer science, FFT, FPGA, Matrix multiplication

April 20, 2011 by hgpu

HPP-Controller: An intra-node controller designed for connecting heterogeneous CPUs

Qiang Li, Panyong Zhang, Ninghui Sun

Tags: Cell processor, Computer science, FPGA, Heterogeneous systems, Memory, Performance

April 19, 2011 by hgpu

Single-Chip Heterogeneous Computing: Does the Future Include Custom Logic, FPGAs, and GPGPUs?

Eric S. Chung, Peter A. Milder, James C. Hoe, Ken Mai

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Tags: ASIC, ATI, ATI CAL, ATI Radeon HD 5870, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance

April 19, 2011 by hgpu

Parallel Approaches for SWAMP Sequence Alignment

Shannon Steinfadt, Kevin Schaffer

Tags: Bioinformatics, Biology, Cell processor, FPGA, nVidia, Sequence alignment, Smith-Waterman algorithm

April 19, 2011 by hgpu

A Hybrid Analytical DRAM Performance Model

George L. Yuan, Tor M. Aamodt

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Tags: Computer science, CUDA, Hardware Architecture, Memory, nVidia

April 19, 2011 by hgpu

Extending the Scalability of Single Chip Stream Processors with On-chip Caches

Ali Bakhoda, Tor M. Aamodt

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Tags: ATI, Computer science, Hardware Architecture, Memory, nVidia

April 19, 2011 by hgpu

A Task-centric Memory Model for Scalable Accelerator Architectures

John H. Kelm, Daniel R. Johnson, Steven S. Lumetta, Matthew I. Frank, Sanjay J. Patel

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Tags: Algorithms, Computer science, Hardware Architecture, Memory model

April 19, 2011 by hgpu

Dynamic warp formation: Efficient MIMD control flow on SIMD graphics hardware

Wilson W. L. Fung, Ivan Sham, George Yuan, Tor M. Aamodt

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce 8800 GTX, Performance, Warp level parallelism

April 19, 2011 by hgpu

Dynamic detection of uniform and affine vectors in GPGPU computations

Sylvain Collange, David Defour, Yao Zhang

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Tags: Algorithms, Computer science, CUDA, Hardware Architecture, nVidia, Optimization, Tesla

April 19, 2011 by hgpu

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

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high performance computing on graphics processing units: hgpu.org

Applications

An efficient GPU implementation of the revised simplex method

Tutorial 3: Methodologies and Performance Impacts of General Purpose Computing on GPUs

Design and implementation of software-managed caches for multicores with local memory

Compressing Floating-Point Number Stream for Numerical Applications

HPP-Controller: An intra-node controller designed for connecting heterogeneous CPUs

Single-Chip Heterogeneous Computing: Does the Future Include Custom Logic, FPGAs, and GPGPUs?

Parallel Approaches for SWAMP Sequence Alignment

A Hybrid Analytical DRAM Performance Model

Extending the Scalability of Single Chip Stream Processors with On-chip Caches

A Task-centric Memory Model for Scalable Accelerator Architectures

Dynamic warp formation: Efficient MIMD control flow on SIMD graphics hardware

Dynamic detection of uniform and affine vectors in GPGPU computations

Recent source codes

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Most viewed papers (last 30 days)