high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Using OpenCL to Implement Median Filtering and RSA Algorithms: Two GPGPU Application Case Studies

Lukas Gillsjo

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Tags: Algorithms, ATI, ATI Radeon R9 280X, Computer science, Filtering, Image processing, nVidia, OpenCL, RSA, Security, Tesla M2050, Thesis

April 4, 2015 by hgpu

Generating Null Models for Large-Scale Networks on GPU

Huan Li, Gang Lu, Junxia Guo

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Tags: C++ AMP, Computer science, Networks, nVidia, nVidia GeForce GTX 480

April 1, 2015 by hgpu

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

J. Briggs, J. Jaykka, J. R. Fergusson, E. P. S. Shellard, S. J. Pennycook

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Tags: Astrophysics, Computer science, Intel Xeon Phi, MPI, OpenMP

April 1, 2015 by hgpu

Massively Parallel Analysis of Similarity Matrices on Heterogeneous Hardware

Tobias Rawald, Mike Sips, Norbert Marwan, Ulf Leser

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Tags: ATI, ATI Radeon HD 7470, Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 690, OpenCL

March 30, 2015 by hgpu

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

Dayong Wang, Anil K. Jain

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, Filtering, Machine learning, Neural networks, nVidia, Tesla K20

March 30, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

Loo.py: From Fortran to performance via transformation and substitution rules

Andreas Klockner

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Tags: Code generation, Computer science, Fortran, OpenCL, Package, Python

March 28, 2015 by hgpu

Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures

Guillaume Chapuis, Hristo Djidjev

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Tags: Computer science, Data Structures and Algorithms, Distributed computing, Distributed data structures, GPU cluster, nVidia, Path problems, Tesla M2090

March 28, 2015 by hgpu

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Xiaowen Chu, Chengjian Liu, Kai Ouyang, Ling Sing Yung, Hai Liu, Yiu-Wing Leung

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Tags: Computer science, CUDA, Error recovery, nVidia, nVidia GeForce GTX 780

March 28, 2015 by hgpu

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Vadim Demchik

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 560 M, nVidia GeForce GTX 780, OpenCL, Package, Pseudo-random number generators, Review, Tesla K40

March 25, 2015 by hgpu

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Cluster computing, Computer science, CUDA, Distributed computing, Energy-efficient computing, GPU cluster, nVidia, Tesla K20

March 25, 2015 by hgpu

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Kamran Karimi

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Tags: ATI, Computer science, OpenCL, OpenMP, Performance

March 25, 2015 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

Using OpenCL to Implement Median Filtering and RSA Algorithms: Two GPGPU Application Case Studies

Generating Null Models for Large-Scale Networks on GPU

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

Massively Parallel Analysis of Similarity Matrices on Heterogeneous Hardware

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Loo.py: From Fortran to performance via transformation and substitution rules

Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

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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