high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Optimizing and Auto-tuning Belief Propagation on the GPU

Scott Grauer-Gray, John Cavazos

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, Optimization, Tesla C870

October 30, 2011 by hgpu

Effective Parallelization of Non-bonded Interactions Kernel for Virtual Screening on GPUs

Gines D. Guerrero, Horacio Perez-Sanchez, Wolfgang Wenzel, Jose M. Cecilia, Jose M. Garcia

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Tags: Bioinformatics, Biology, CUDA, nVidia, Optimization, Pharmaceuticals, Tesla C1060

October 30, 2011 by hgpu

Intermediate Language Extensions for Parallelism

Jisheng Zhao, Vivek Sarkar

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Tags: Computer science, Java, Optimization, Programming techniques

October 30, 2011 by hgpu

Development and evaluation of a GPU-optimized N-body term for the simulation of biomolecules

Timo Strunk, Moritz Wolf, Wolfgang Wenzel

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Biology, Biomolecules, Monte Carlo simulation, N-body simulation, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization

October 30, 2011 by hgpu

Compiling Stream Applications for Heterogeneous Architectures

Amir H. Hormati

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Tags: Compilers, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Optimization, Tesla C2050, Thesis

October 28, 2011 by hgpu

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Long Zheng, Yanchao Lu, Mengwei Ding, Yao Shen, Minyi Guo, Song Guo

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Optimization

October 28, 2011 by hgpu

Implementing Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Kunle Olukotun, Tiark Rompf, Martin Odersky

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Optimization, Tesla C2050

October 28, 2011 by hgpu

Techniques to maximize memory bandwidth on the Rigel compute accelerator

William J. Tuohy

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Tags: ATI, ATI Radeon HD 5870, Computer science, Memory, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10, Thesis

October 27, 2011 by hgpu

An Evolutionary Optimization Strategy Using Graphics Processing Units to Efficiently Investigate Gene-Gene Interactions in Genetic Association Studies

Joel B. Fontanarosa, Yang Dai

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Tags: Algorithms, Biology, CUDA, Evolutionary Computations, Genetics, nVidia, nVidia GeForce GTX 470, Optimization

October 25, 2011 by hgpu

Optimizing a Near-duplicate Document Detection System with SIMD Technologies

Xinpan Yuan, Jun Long, Hao Zhang, Zuping Zhang, Weihua Gui

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Tags: Algorithms, Clustering, Computer science, nVidia, nVidia GeForce 8600 GT, OpenCL, Optimization

October 24, 2011 by hgpu

Design and Implementation of Centrally-Coordinated Peer-to-Peer Live-streaming

Roberto Roverso

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Tags: Algorithms, Computer science, Consensus, CUDA, Network communications, Networks, nVidia, nVidia GeForce GTX 295, Optimization, Thesis

October 23, 2011 by hgpu

Analyzing Soft-Error Vulnerability on GPGPU Microarchitecture

Jingweijia Tan, Nilanjan Goswami, Tao Li, Xin Fu

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Tags: Computer science, CUDA, nVidia, Optimization, PTX

October 23, 2011 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimizing and Auto-tuning Belief Propagation on the GPU

Effective Parallelization of Non-bonded Interactions Kernel for Virtual Screening on GPUs

Intermediate Language Extensions for Parallelism

Development and evaluation of a GPU-optimized N-body term for the simulation of biomolecules

Compiling Stream Applications for Heterogeneous Architectures

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Implementing Domain-Specific Languages for Heterogeneous Parallel Computing

Techniques to maximize memory bandwidth on the Rigel compute accelerator

An Evolutionary Optimization Strategy Using Graphics Processing Units to Efficiently Investigate Gene-Gene Interactions in Genetic Association Studies

Optimizing a Near-duplicate Document Detection System with SIMD Technologies

Design and Implementation of Centrally-Coordinated Peer-to-Peer Live-streaming

Analyzing Soft-Error Vulnerability on GPGPU Microarchitecture

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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