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Performance Drawbacks for Matrix Multiplication using Set Associative Cache in GPU devices

Leonid Djinevski, Sime Arsenovski, Sasko Ristov, Marjan Gusev

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 680, Performance

August 19, 2013 by hgpu

GPU Programming in Functional Languages: A Comparison of Haskell GPU Embedded Domain Specific Languages

C. Ouwehand, P. Hijma, W.J. Fokkink

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Tags: Computer science, CUDA, Haskell, Matrix multiplication, nVidia, nVidia GeForce GTX 480

August 6, 2013 by hgpu

OpenCL API Extensions to achieve Multi-level Parallelism for Efficient Implementation of Strassen’s Matrix Multiplication on GPUs

Sivaramakrishnan Kasiviswanathan

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Tags: Algorithms, Computer science, Data parallelism, Matrix multiplication, nVidia, OpenCL, Tesla K20

July 19, 2013 by hgpu

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

Muhammed Al-Mulhem, Abdulah AlDhamin, Raed Al-Shaikh

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Tags: Algorithms, Benchmarking, Bioinformatics, Computer science, CUDA, Linear Algebra, Matrix multiplication, MPI, nVidia, nVidia GeForce GTX 460

July 19, 2013 by hgpu

CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs

C. E. Castro, J. Behrens, C. Pelties

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Tags: CUDA, Differential equations, Earth and Space Sciences, Geoscience, Hyperbolic PDEs, Matrix multiplication, nVidia, Partial differential equations, PDEs, Tesla C2070

July 15, 2013 by hgpu

Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

Joe Jackson

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Tags: Computer science, CUDA, Energy-efficient computing, Matrix multiplication, nVidia, nVidia GeForce 9800 GT, OpenCL

July 8, 2013 by hgpu

Comparison of Rectangular Matrix Multiplication with and without Border Conditions

Petre Lameski, Igor Mishkovski, Sonja Filiposka, Dimitar Trajanov, Leonid Djinevski

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 680

July 7, 2013 by hgpu

GPU Matrix Multiplication

Junjie Li, Sanjay Ranka, Sartaj Sahni

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Tesla C1060

June 18, 2013 by hgpu

FastSpMM: An Efficient Library for Sparse Matrix Matrix Product on GPUs

Gloria Ortega, Francisco Vazquez, Inmaculada Garcia, Ester M. Garzon

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Source codes

Tags: Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 480, Package, Sparse matrix, Tesla C2050

June 12, 2013 by hgpu

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Rafael Alejandro Vejarano, Phuong Thi Yen, Jeong-Gun Lee

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Tags: Computer science, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 460, OpenCL, Performance

June 4, 2013 by hgpu

Analyzing Locality of Memory References in GPU Architectures

Saurabh Gupta, Ping Xiang, Huiyang Zhou

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Tags: Computer science, GPGPU-sim, Matrix multiplication, nVidia, nVidia GeForce GTX 480

May 16, 2013 by hgpu

A portable and high-performance matrix operations library for CPUs, GPUs and beyond

Rahul Garg, Laurie Hendren

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 7970, Computer science, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Tesla C2050

May 11, 2013 by hgpu

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

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

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high performance computing on graphics processing units: hgpu.org

Performance Drawbacks for Matrix Multiplication using Set Associative Cache in GPU devices

GPU Programming in Functional Languages: A Comparison of Haskell GPU Embedded Domain Specific Languages

OpenCL API Extensions to achieve Multi-level Parallelism for Efficient Implementation of Strassen’s Matrix Multiplication on GPUs

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs

Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

Comparison of Rectangular Matrix Multiplication with and without Border Conditions

GPU Matrix Multiplication

FastSpMM: An Efficient Library for Sparse Matrix Matrix Product on GPUs

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Analyzing Locality of Memory References in GPU Architectures

A portable and high-performance matrix operations library for CPUs, GPUs and beyond

Recent source codes

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

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

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