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Mars: Accelerating MapReduce with Graphics Processors

Wenbin Fang, Bingsheng He, Qiong Luo, N.K. Govindaraju

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Tags: Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 280, Package, Presentation

July 17, 2011 by hgpu

A new parallel video understanding and retrieval system

Ke-yan Liu, Tong Zhang, Lei Wang

Tags: Image processing, Image recognition, MapReduce, nVidia, nVidia Quadro FX 4600

June 7, 2011 by hgpu

MapCG: writing parallel program portable between CPU and GPU

Chuntao Hong, Dehao Chen, Wenguang Chen, Weimin Zheng, Haibo Lin

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Tags: Computer science, CUDA, High-level Languages, MapReduce, nVidia, nVidia GeForce GTX 280, Programming techniques

June 2, 2011 by hgpu

MITHRA: Multiple data independent tasks on a heterogeneous resource architecture

Reza Farivar, Abhishek Verma, Ellick M. Chan, Roy H. Campbell

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce 9800 GX2, nVidia Quadro FX 570

April 22, 2011 by hgpu

Four styles of parallel and net programming

Zhiwei Xu, Yongqiang He, Wei Lin, Li Zha

Tags: Computer science, CUDA, MapReduce, nVidia, Programming techniques

January 8, 2011 by hgpu

Multi-GPU volume rendering using MapReduce

Jeff A. Stuart, Cheng-Kai Chen, Kwan-Liu Ma, John D. Owens

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Tags: Computer science, CUDA, GPU cluster, MapReduce, nVidia, Rendering, Tesla C1090

December 25, 2010 by hgpu

Map-reduce as a Programming Model for Custom Computing Machines

Jackson H. C. Yeung, C. C. Tsang, K. H. Tsoi, Bill S. H. Kwan, Chris C. C. Cheung, Anthony P. C. Chan, Philip H. W. Leong

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Tags: Computer science, CUDA, FPGA, MapReduce, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GTX, Signal processing

December 12, 2010 by hgpu

A map reduce framework for programming graphics processors

Bryan Catanzaro, Narayanan Sundaram, Kurt Keutzer

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Tags: Computer science, CUDA, MapReduce, nVidia, nVidia GeForce 8800 GTX

December 12, 2010 by hgpu

Fast support vector machine training and classification on graphics processors

Bryan Catanzaro, Narayanan Sundaram, Kurt Keutzer

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Tags: Algorithms, Computer science, CUDA, MapReduce, nVidia, nVidia GeForce 8800 GTX

December 7, 2010 by hgpu

A Massively Parallel Architecture for Bioinformatics

Gerd Pfeiffer, Stefan Baumgart, Jan Schroder, Manfred Schimmler

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Tags: Algorithms, Bioinformatics, Biology, FPGA, MapReduce

November 27, 2010 by hgpu

Mars: a MapReduce framework on graphics processors

Bingsheng He, Wenbin Fang, Qiong Luo, Naga K. Govindaraju, Tuyong Wang

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Tags: Computer science, CUDA, Data parallelism, MapReduce, nVidia, nVidia GeForce 8800 GTX, Package, Programming techniques, Web Analysis

October 30, 2010 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

Mars: Accelerating MapReduce with Graphics Processors

A new parallel video understanding and retrieval system

MapCG: writing parallel program portable between CPU and GPU

MITHRA: Multiple data independent tasks on a heterogeneous resource architecture

Four styles of parallel and net programming

Multi-GPU volume rendering using MapReduce

Map-reduce as a Programming Model for Custom Computing Machines

A map reduce framework for programming graphics processors

Fast support vector machine training and classification on graphics processors

A Massively Parallel Architecture for Bioinformatics

Mars: a MapReduce framework on graphics processors

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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