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A fight for performance and accuracy of the matrix multiplication routines: CUBLAS on Nvidia Tesla versus MKL and ATLAS on Intel Nehalem

Philippe Estival, Luc Giraud

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla T10

May 29, 2012 by hgpu

An MPI-CUDA Implementation and Optimization for Parallel Sparse Equations and Least Squares (LSQR)

He Huang, Liqiang Wang, En-Jui Lee, Po Chen

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Tags: Computer science, CUBLAS, CUDA, Earth and Space Sciences, Geoscience, MPI, nVidia, Optimization, Tesla C2050, Tesla M2070

May 19, 2012 by hgpu

Performance Exploration of Selected Manually and Automatically Parallelized Codes on GPUs

Franz Xaver Bayerl

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Tags: Code generation, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 560 Ti, Performance, Thesis

April 19, 2012 by hgpu

Auto-tuning Dense Vector and Matrix-Vector Operations for Fermi GPUs

Hans Henrik Brandenborg Sorensen

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Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050

April 18, 2012 by hgpu

High-Performance Matrix-Vector Multiplication on the GPU

Hans Henrik Brandenborg Sorensen

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Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050

April 18, 2012 by hgpu

Bound the Peak Performance of SGEMM on GPU with software-controlled fast memory

Junjie Lai, Andre Seznec

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Tags: Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 580, Performance

April 7, 2012 by hgpu

Parallel Semi-Implicit Time Integrators

B. Ong, A. Melfi, A. Christlieb

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Partial differential equations, PDEs, Tesla C1060

February 9, 2012 by hgpu

CUDA Expression Templates

Paul Wiemann, Stephan Wenger, Marcus Magnor

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Source codes

Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTS 250, Package

January 30, 2012 by hgpu

Cost Efficient PageRank Computation using GPU

Praveen K., Vamshi Krishna K., Anil Sri Harsha B., S. Balasubramanian, P.K. Baruah

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Tags: Algorithms, Computer science, CUBLAS, CUDA, List ranking, nVidia, Sparse matrix, Tesla T20

January 24, 2012 by hgpu

Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS

Maxim Naumov

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050

January 12, 2012 by hgpu

Applying OOC Techniques in the Reduction to Condensed Form for Very Large Symmetric Eigenproblems on GPUs

Davor Davidovic, Enrique S. Quintana-Orti

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Tags: Algorithms, CUBLAS, CUDA, Linear Algebra, Mathematics, nVidia, Tesla C2050

January 6, 2012 by hgpu

Optimising the DBCSR GPU Implementation

Jay Chetty

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla C2050, Thesis

December 31, 2011 by hgpu

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

See all packages

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high performance computing on graphics processing units: hgpu.org

A fight for performance and accuracy of the matrix multiplication routines: CUBLAS on Nvidia Tesla versus MKL and ATLAS on Intel Nehalem

An MPI-CUDA Implementation and Optimization for Parallel Sparse Equations and Least Squares (LSQR)

Performance Exploration of Selected Manually and Automatically Parallelized Codes on GPUs

Auto-tuning Dense Vector and Matrix-Vector Operations for Fermi GPUs

High-Performance Matrix-Vector Multiplication on the GPU

Bound the Peak Performance of SGEMM on GPU with software-controlled fast memory

Parallel Semi-Implicit Time Integrators

CUDA Expression Templates

Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS

Applying OOC Techniques in the Reduction to Condensed Form for Very Large Symmetric Eigenproblems on GPUs

Optimising the DBCSR GPU Implementation

Recent source codes

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

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