high performance computing on graphics processing units: hgpu.org

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HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

E.M. Garzón, J.A. Martínez, J.J. Moreno, M.L. Puertas

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Tags: Algorithms, Computer science, CUDA, Graph theory, HPC, nVidia, OpenMP, Package, Tesla V100

September 29, 2024 by hgpu

Supercharging Federated Learning with Flower and NVIDIA FLARE

Holger R. Roth, Daniel J. Beutel, Yan Cheng, Javier Fernandez Marques, Heng Pan, Chester Chen, Zhihong Zhang, Yuhong Wen, Sean Yang, Isaac (Te-Chung)Yang, Yuan-Ting Hsieh, Ziyue Xu, Daguang Xu, Nicholas D. Lane, Andrew Feng

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Tags: AI, Algorithms, Computer science, nVidia, Package, Security

July 7, 2024 by hgpu

GPU Implementations for Midsize Integer Addition and Multiplication

Cosmin E. Oancea, Stephen M. Watt

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia A100, Performance, Programming Languages

May 26, 2024 by hgpu

Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

Andres E. Tomas, Enrique S. Quintana-Orti, Hartwig Anzt

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100

March 18, 2024 by hgpu

A Review of the Parallelization Strategies for Iterative Algorithms

Xingxing Zhou, Ming Ling, Shidi Tang, YanXiang Zhu

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Data parallelism, OpenCL

December 3, 2023 by hgpu

RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs

Benjamin Brock, Aydın Buluç, Katherine Yelick

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, MPI, nVidia, nVidia DGX-2, Sparse matrix, Tesla V100

December 3, 2023 by hgpu

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

Hyun Park, Parth Patel, Roland Haas, E. A. Huerta

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Tags: AI, Algorithms, Biology, Biomolecules, Biophysics, nVidia, nVidia A100, nVidia A40, Package

August 20, 2023 by hgpu

Fast Knowledge Graph Completion using Graphics Processing Units

Chun-Hee Lee, Dong-oh Kang, Hwa Jeon Song

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Tags: AI, Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, nVidia A100

July 30, 2023 by hgpu

Tile-based Lightweight Integer Compression in GPU

Anil Shanbhag, Bobbi W. Yogatama, Xiangyao Yu, Samuel Madden

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia V100, Package

July 16, 2023 by hgpu

Matrix Multiplication Using Only Addition

Daniel Cussen, Jeffrey D. Ullman

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Tags: Algorithms, Computer science, Matrix multiplication

July 9, 2023 by hgpu

cuSLINK: Single-linkage Agglomerative Clustering on the GPU

Corey J. Nolet, Divye Gala, Alex Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Hierarchical clustering, Machine learning, Nearest neighbour, nVidia, nVidia A100, nVidia DGX-1, Package

July 2, 2023 by hgpu

ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code

Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña

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Tags: Algorithms, Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla A100

June 25, 2023 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Programming

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

Supercharging Federated Learning with Flower and NVIDIA FLARE

GPU Implementations for Midsize Integer Addition and Multiplication

Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

A Review of the Parallelization Strategies for Iterative Algorithms

RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

Fast Knowledge Graph Completion using Graphics Processing Units

Tile-based Lightweight Integer Compression in GPU

Matrix Multiplication Using Only Addition

cuSLINK: Single-linkage Agglomerative Clustering on the GPU

ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code

Recent source codes

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Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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