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New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Neelima Reddy, Raghavendra Prakash, Ram Mohana Reddy

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 470, Sparse matrix

August 1, 2012 by hgpu

Sparse Matrix-Vector Multiplication on NVIDIA GPU

Hui Liu, Song Yu, Zhangxin Chen, Ben Hsieh, Lei Shao

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050, Tesla C2070

July 16, 2012 by hgpu

Sparse Matrix Matrix Multiplication on Hybrid CPU+GPU Platforms

Kiran Kumar Matam, Siva Rama Krishna Bharadwaj, Kishore Kothapalli

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Optimization, Sparse matrix, Tesla C2050

July 16, 2012 by hgpu

Stencil-Aware GPU Optimization of Iterative Solvers

Chekuri Choudary, Jeswin Godwin, Justin Holewinski, Deepan Karthik, Daniel Lowell, Azamat Mametjanov, Boyana Norris, Gerald Sabin, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, Optimization, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070

July 11, 2012 by hgpu

Elastically Deformable Models based on the Finite Element Method Accelerated on Graphics Hardware using CUDA

Mickeal Verschoor, Andrei C. Jalba

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 570, Sparse matrix

July 9, 2012 by hgpu

Autotuning Stencil-Based Computations on GPUs

Azamat Mametjanov, Daniel Lowell, Ching-Chen May, Boyana Norris

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Tags: Computer science, CUDA, Differential equations, nVidia, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C1060, Tesla C2070

June 9, 2012 by hgpu

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Bor-Yiing Su, Kurt Keutzer

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Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

May 30, 2012 by hgpu

Effective Sparse Matrix Representation for the GPU Architectures

B. Neelima, Prakash S. Raghavendra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 525 M, Optimization, Sparse matrix

May 25, 2012 by hgpu

The Linear Direct Sparse Solver on GPU for Bundle Adjustment Method

Ivaneik Ondrej, Ivan Simecek

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 570, Package, Sparse matrix, Thesis

May 19, 2012 by hgpu

Accurate CUDA Performance Modeling for Sparse Matrix-Vector Multiplication

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 19, 2012 by hgpu

The BiConjugate gradient method on GPUs

G. Ortega, E. M. Garzon, F. Vazquez, I. Garcia

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 15, 2012 by hgpu

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Jeswin Godwin, Justin Holewinski, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla C2050

April 25, 2012 by hgpu

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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high performance computing on graphics processing units: hgpu.org

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Sparse Matrix-Vector Multiplication on NVIDIA GPU

Sparse Matrix Matrix Multiplication on Hybrid CPU+GPU Platforms

Stencil-Aware GPU Optimization of Iterative Solvers

Elastically Deformable Models based on the Finite Element Method Accelerated on Graphics Hardware using CUDA

Autotuning Stencil-Based Computations on GPUs

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Effective Sparse Matrix Representation for the GPU Architectures

The Linear Direct Sparse Solver on GPU for Bundle Adjustment Method

Accurate CUDA Performance Modeling for Sparse Matrix-Vector Multiplication

The BiConjugate gradient method on GPUs

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Recent source codes

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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