high performance computing on graphics processing units: hgpu.org

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A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Kooktae Lee, Raktim Bhattacharya, Vijay Gupta

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2050

March 18, 2015 by hgpu

Heterogeneous Acceleration of Volumetric JPEG 2000

Jan G. Cornelis, Jan Lemeire, Tim Bruylants, Peter Schelkens

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Tags: ATI, ATI Radeon HD 7950, Heterogeneous systems, Image processing, JPEG2000, nVidia, nVidia GeForce GTX 650 Ti, OpenCL, Tesla C2050

March 14, 2015 by hgpu

Counting Triangles in Large Graphs on GPU

Adam Polak

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

March 3, 2015 by hgpu

High performance methods for frequent pattern mining

Lan Vu

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, Tesla C2050, Thesis

February 22, 2015 by hgpu

Fast Subgraph Matching on Large Graphs using Graphics Processors

Ha-Nguyen Tran, Jung-jae Kim, Bingsheng He

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

February 9, 2015 by hgpu

Tangram: a High-level Language for Performance Portable Code Synthesis

Li-Wen Chang, Abdul Dakkak, Christopher I. Rodrigues, Wen-mei Hwu

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Tags: Computer science, High-level Languages, nVidia, OpenCL, Tesla C2050

January 26, 2015 by hgpu

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Ana Lucia Varbanescu, Merijn Verstraaten, Cees de Laat, Ate Penders, Alexandru Iosup, Henk Sips

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C2050

January 23, 2015 by hgpu

Harnessing Aspect Oriented Programming on GPU: Application to Warp-Level Parallelism (WLP)

Jonathan Passerat-Palmbach, Pierre Schweitzer, Jonathan Caux, Pridi Siregar, Claude Mazel, David Hill

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Tags: Computer science, CUDA, nVidia, Stochastic simulation, Tesla C2050, Warp level parallelism

January 19, 2015 by hgpu

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

Shinichi Yamagiwa, Guyue Wang, Koichi Wada

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Tags: Computer science, CUDA, nVidia, OpenCL, Tesla C2050

January 13, 2015 by hgpu

GPGPU-Sim

Filip Andersson

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Tesla C2050, Thesis

December 22, 2014 by hgpu

Efficient Workload Balancing on Heterogeneous GPUs using Mixed-Integer Non-Linear Programming

Chih-Sheng Lin, Chih-Wei Hsieh, Hsi-Ya Chang, Pao-Ann Hsiung

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 690, Tesla C2050, Tesla K20

December 20, 2014 by hgpu

Compiler-Level Explicit Cache for a GPGPU Programming Framework

Tomoharu Kamiya, Takanori Maruyama, Kazuhiko Ohno, Masaki Matsumoto

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Tesla C2050, Tesla K20

December 12, 2014 by hgpu

VFLog: vertical + gpu + free join + datalog

Column-Oriented Datalog on the GPU

ViVid Project

Exploring data flow design and vectorization with oneAPI for streaming applications on CPU+GPU

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

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high performance computing on graphics processing units: hgpu.org

A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Heterogeneous Acceleration of Volumetric JPEG 2000

Counting Triangles in Large Graphs on GPU

High performance methods for frequent pattern mining

Fast Subgraph Matching on Large Graphs using Graphics Processors

Tangram: a High-level Language for Performance Portable Code Synthesis

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Harnessing Aspect Oriented Programming on GPU: Application to Warp-Level Parallelism (WLP)

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

GPGPU-Sim

Efficient Workload Balancing on Heterogeneous GPUs using Mixed-Integer Non-Linear Programming

Compiler-Level Explicit Cache for a GPGPU Programming Framework

Recent source codes

VFLog: vertical + gpu + free join + datalog

ViVid Project

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

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