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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

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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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

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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