high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Counting and Occurrence Sort for GPUs using an Embedded Language

Josef Svenningsson, Bo Joel Svensson, Mary Sheeran

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Tags: Algorithms, Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 670, Package, Sorting

July 30, 2013 by hgpu

Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

Jack Dongarra, Mark Gates, Azzam Haidar, Yulu Jia, Khairul Kabir, Piotr Luszczek, Stanimire Tomov

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Tags: Computer science, Heterogeneous systems, Intel Phi, Linear Algebra, Package, Programming techniques

July 30, 2013 by hgpu

PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs

L.Yu. Barash, L.N. Shchur

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Tags: Algorithms, Computational Physics, Computer science, CUDA, Mathematical Software, nVidia, Package, Pseudo-random number generators, Tesla C2050

July 25, 2013 by hgpu

The Astrophysical Multipurpose Software Environment

F.I. Pelupessy, A. van Elteren, N. de Vries, S.L.W. McMillan, N. Drost, S.F. Portegies Zwart

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, MPI, nVidia, Package, Python

July 21, 2013 by hgpu

Image reconstruction in digital holographic microscopy on GPU

Andrej Krejcir

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Tags: Algorithms, CUDA, Image processing, Image reconstruction, Microscopy, nVidia, nVidia GeForce GTX 470, Optimization, Package, Thesis

July 21, 2013 by hgpu

GPU Computing in Economics

Eric M. Aldrich

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Tags: CUDA, Finance, nVidia, Package, Review, Tesla C2075

July 20, 2013 by hgpu

Early Experiences With The OpenMP Accelerator Model

Chunhua Liao, Yonghong Yan, Bronis R. de Supinski, Daniel J. Quinlan, Barbara Chapman

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Package, Tesla K20

July 17, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

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Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Nicholas Wilt

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Tags: Book, Computer science, CUDA, Image processing, N-body simulation, nVidia, Overview, Package

July 13, 2013 by hgpu

Parallel Graph Processing on Graphics Processors Made Easy

Jianlong Zhong, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

July 12, 2013 by hgpu

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

Nouredine Melab, The van Luong, Karima Boufaras, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package, Performance, Search

July 8, 2013 by hgpu

CrowdCL: Web-Based Volunteer Computing with WebCL

Tommy MacWilliam, Cris Cecka

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Tags: Computer science, Distributed computing, Java, nVidia, nVidia GeForce GT 320 M, OpenCL, Package, Tesla K20

July 7, 2013 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

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

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high performance computing on graphics processing units: hgpu.org

Applications

Counting and Occurrence Sort for GPUs using an Embedded Language

Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs

The Astrophysical Multipurpose Software Environment

Image reconstruction in digital holographic microscopy on GPU

GPU Computing in Economics

Early Experiences With The OpenMP Accelerator Model

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Parallel Graph Processing on Graphics Processors Made Easy

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

CrowdCL: Web-Based Volunteer Computing with WebCL

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

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

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