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RealTime GPU-Based Motion Planning for Task Executions

Chonhyon Park, Jia Pan, Dinesh Manocha

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680

April 29, 2013 by hgpu

Fast Makespan Estimation for GPU Threads on a Single Streaming Multiprocessor

Kostiantyn Berezovskyi, Konstantinos Bletsas, Stefan M. Petters

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 680, PTX, Timing analysis

April 22, 2013 by hgpu

Computing Privacy-Preserving Edit Distance and Smith-Waterman Problems on the GPU Architecture

Shi Pu, Jyh-Charn Liu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Security, Smith-Waterman algorithm

April 18, 2013 by hgpu

Communication-Minimizing 2D Convolution in GPU Registers

Forrest N. Iandola, David Sheffield, Michael Anderson, Phitchaya Mangpo Phothilimthana, Kurt Keutzer

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 680, Prefetch, Tesla C2050

April 17, 2013 by hgpu

Real-time Subsurface Scattering for Particle-based Fluids using Finite Volume Method

Kyung-Kyu Kang, Dongho Kim

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Tags: Computer science, CUDA, Diffusion equation, Finite volume method, Fluid simulation, GLSL, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenGL, Rendering, Voronoi diagram

April 12, 2013 by hgpu

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

R. Capuzzo-Dolcettaa, M. Spera

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, ATI Radeon HD 7870, ATI Radeon HD 7970, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Tesla C1060, Tesla C2050, Tesla K20

April 9, 2013 by hgpu

Adapting Particle Filter Algorithms to Many-Core Architectures

Mehdi Chitchian, Alexander S. van Amesfoort, Andrea Simonetto, Tamas Keviczky, Henk J. Sips

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Source codes

Tags: Algorithms, ATI, ATI Radeon HD 6970, ATI Radeon HD 7970, Bayesian, Computer science, Computer vision, CUDA, Filtering, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Particle filtering

April 4, 2013 by hgpu

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Jianlong Zhong, Bingsheng He

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, PTX, Task scheduling, Tesla C2050

March 23, 2013 by hgpu

Parallelization with Different API on Multicore Architecture

Georg Rempfer

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Tags: Chemistry, CUDA, Liquid crystals, nVidia, nVidia GeForce GTX 680, Physics, Statistical Mechanics, Thesis

March 18, 2013 by hgpu

GPU Accelerated Multiple Deoxyribose Nucleic Acid Sequence Parallel Matching

Gang Liao, Qi Sun, Longfei Ma, Zhihui Qin

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 680, Sequence matching, Suffix trees

March 18, 2013 by hgpu

Exploring power efficiency and optimizations targeting heterogeneous applications

Yash Sanjeev Ukidave

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Tags: AMD Fusion, ATI, ATI Radeon HD 7770, Computer science, Energy-efficient computing, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, Thesis

March 16, 2013 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

RealTime GPU-Based Motion Planning for Task Executions

Fast Makespan Estimation for GPU Threads on a Single Streaming Multiprocessor

Computing Privacy-Preserving Edit Distance and Smith-Waterman Problems on the GPU Architecture

Communication-Minimizing 2D Convolution in GPU Registers

Real-time Subsurface Scattering for Particle-based Fluids using Finite Volume Method

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

Adapting Particle Filter Algorithms to Many-Core Architectures

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Parallelization with Different API on Multicore Architecture

GPU Accelerated Multiple Deoxyribose Nucleic Acid Sequence Parallel Matching

Exploring power efficiency and optimizations targeting heterogeneous applications

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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