high performance computing on graphics processing units: hgpu.org

hgpu.org » Applications

Dark Sky Simulations: Early Data Release

Samuel W. Skillman, Michael S. Warren, Matthew J. Turk, Risa H. Wechsler, Daniel E. Holz, P. M. Sutter

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Package, Python, Tesla K20

July 22, 2014 by hgpu

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

Christopher Schuster

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Package, SAT

July 16, 2014 by hgpu

CUD@SAT: SAT Solving on GPUs

Alessandro Dal Pal'u, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Computer science, CUDA, Numerical simulation, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, Package, SAT, Tesla C2075

July 15, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 by hgpu

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Charalampos S. Kouzinopoulos, John-Alexander M. Assael, Themistoklis K. Pyrgiotis, Konstantinos G. Margaritis

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Tags: Algorithms, Computer science, CUDA, Databases, GPU cluster, MPI, nVidia, nVidia GeForce GT 240, Package, Tesla S1070

July 11, 2014 by hgpu

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Hasse Lovgren

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Tags: ATI, ATI Radeon HD 5870, Computer science, Mathematics, Neural networks, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Tesla C1060, Thesis

July 9, 2014 by hgpu

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Bartosz D. Wozniak

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Tags: CUBLAS, CUDA, Fluid dynamics, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Package, Python, Tesla K40, Thesis

July 7, 2014 by hgpu

Latency considerations of depth-first GPU ray tracing

M. Guthe

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Tags: 3D Graphics and Realism, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Raytracing

July 7, 2014 by hgpu

SimCommSys: taking the errors out of error-correcting code simulations

Johann A. Briffa, Stephan Wesemeyer

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Tags: Computer science, CUDA, Error recovery, nVidia, Package, Python

July 6, 2014 by hgpu

Writing self-adaptive codes for heterogeneous systems

Jorge F. Fabeiro, Diego Andrade, Basilio B. Fraguela, Ramon Doallo

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla K20

July 4, 2014 by hgpu

The design and verification of Mumax3

Arne Vansteenkiste, Jonathan Leliaert, Mykola Dvornik, Felipe Garcia-Sanchez, Bartel Van Waeyenberge

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Tags: Computational Physics, CUDA, Image generation, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX Titan, Package, Physics

July 1, 2014 by hgpu

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

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high performance computing on graphics processing units: hgpu.org

Packages

Dark Sky Simulations: Early Data Release

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

CUD@SAT: SAT Solving on GPUs

Benchmarking the Memory Hierarchy of Modern GPUs

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Latency considerations of depth-first GPU ray tracing

SimCommSys: taking the errors out of error-correcting code simulations

Writing self-adaptive codes for heterogeneous systems

The design and verification of Mumax3

Recent source codes

XaaS containers

microSYCL: SYCL micro-benchmarks repository

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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