high performance computing on graphics processing units: hgpu.org

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Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Erik Zenker, Rene Widera, Axel Hubl, Guido Juckeland, Andreas Knupfer, Wolfgang E. Nagel, Michael Bussmann

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Package, Particle-in-cell methods, Physics, Plasma physics, Programming techniques, Tesla K80

June 14, 2016 by hgpu

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

M. Abalenkovs, A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, A. YarKhan

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Programming techniques, Review, Tesla K40

April 19, 2016 by hgpu

Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures

Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar

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Tags: Algorithms, Compilers, Computer science, Heterogeneous systems, nVidia, OpenCL, Programming techniques, Tesla M2050

March 10, 2016 by hgpu

Auto-Vectorizing a Large-scale Production Unstructured-mesh CFD Application

G.R. Mudalige, I.Z. Reguly, M.B. Giles

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Tags: cfd, Code generation, Computer science, CUDA, Fluid dynamics, Fortran, nVidia, Programming techniques, Tesla K80

February 25, 2016 by hgpu

Performance Analysis of GPU-Accelerated Filter-Based Source Finding for HI Spectral Line Image Data

Stefan Westerlund, Christopher Harris

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Tags: Astrophysics, CUDA, Filtering, Instrumentation and Methods for Astrophysics, MPI, nVidia, OpenCL, Programming techniques, Tesla C2075

July 20, 2015 by hgpu

Optimized Data Transfers Based on the OpenCL Event Management Mechanism

Hiroyuki Takizawa, Shoichi Hirasawa, Makoto Sugawara, Isaac Gelado, Hiroaki Kobayashi, Wen-mei W. Hwu

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Tags: Computer science, nVidia, nVidia GeForce GTX Titan, OpenCL, Programming techniques, Tesla C1060, Tesla C2070

February 1, 2015 by hgpu

Heterogeneous computing with an algorithmic skeleton framework

Fabio Miguel Cardoso Soldado

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, Heterogeneous systems, OpenCL, Programming techniques, Thesis

October 20, 2014 by hgpu

Teaching Parallel Programming Using Java

Aamir Shafi, Aleem Akhtar, Ansar Javed, Bryan Carpenter

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Tags: Computer science, CUDA, Education, Hadoop, Java, MapReduce, MPI, nVidia, Programming techniques, Software Engineering

October 4, 2014 by hgpu

The GPUVerify Method: a Tutorial Overview

Alastair F. Donaldson

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Tags: Computer science, CUDA, nVidia, OpenCL, Overview, Package, Programming techniques, Tutorial

September 16, 2014 by hgpu

Cell Charge Approximation for Accelerating Molecular Simulation on CUDA-Enabled GPU

Shyam Mohan K T, Jayaraj P B

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Tags: Chemistry, CUDA, Electrostatics, Molecular dynamics, Molecular simulation, nVidia, Programming techniques

August 7, 2014 by hgpu

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Istvan Zoltan Reguly

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Tags: Algorithms, Code generation, Computer science, CUDA, Differential equations, FEM, Finite element method, Finite volume method, Fluid dynamics, Heterogeneous systems, Linear Algebra, nVidia, Partial differential equations, PDEs, Programming techniques, Tesla C2070, Tesla K20, Tesla K40, Thesis

July 24, 2014 by hgpu

Parallelized Hierarchical Expected Matching Probability for Multiple Sequence Alignment

Kedhar M, DR. M. Rajasekhara Babu, Mayank G, Abhinivesh M

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Tags: Bioinformatics, Biology, CUDA, nVidia, Programming techniques, RNA, Sequence alignment, Tesla C2070

July 12, 2014 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

Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures

Auto-Vectorizing a Large-scale Production Unstructured-mesh CFD Application

Performance Analysis of GPU-Accelerated Filter-Based Source Finding for HI Spectral Line Image Data

Optimized Data Transfers Based on the OpenCL Event Management Mechanism

Heterogeneous computing with an algorithmic skeleton framework

Teaching Parallel Programming Using Java

The GPUVerify Method: a Tutorial Overview

Cell Charge Approximation for Accelerating Molecular Simulation on CUDA-Enabled GPU

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Parallelized Hierarchical Expected Matching Probability for Multiple Sequence Alignment

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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