high performance computing on graphics processing units: hgpu.org

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Real-Time Hair Rendering

Markus Rapp

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce GTX 580, OpenGL, Rendering, Tessellation, Thesis

December 2, 2014 by hgpu

SiftCU: An Accelerated Cuda Based Implementation of SIFT

Mahdi S. Mohammadi, Mehdi Rezaeian

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 440 GT, nVidia GeForce GTX 670, Package

December 2, 2014 by hgpu

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Nam-Luc Tran, Sabri Skhiri, Arnaud Schils, Edgar Isaac Hiroshi Leon Saiki

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan, Package

December 2, 2014 by hgpu

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

Naresh Balaji, Esin Yavuz, Thomas Nowotny

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Tags: Algorithms, Code generation, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GT 755 M, Package

December 2, 2014 by hgpu

GPU accelerated feature algorithms for mobile devices

Seth Hall

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Tags: Algorithms, Augmented reality, Clustering, Computer science, Computer vision, OpenCV, OpenGL, Thesis

December 2, 2014 by hgpu

An Open-Source GPU-Accelerated Feature Extraction Tool

Josef Michalek, Jan Vanek

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 660, OpenCL, Speech recognition

December 1, 2014 by hgpu

GPU Declarative Framework

Robert W. Senser, Jr.

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Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Chih-Sheng Lin

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 690, OpenCL, Task scheduling, Tesla C2050, Thesis

December 1, 2014 by hgpu

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

G.R. Mudalige, I.Z. Reguly, M.B. Giles, A.C. Mallinson, W.P. Gaudin, J.A. Herdman

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenACC, OpenCL, Tesla K20

December 1, 2014 by hgpu

pyMIC: A Python Offload Module for the Intel Xeon Phi Coprocessor

Michael Klemm, Jussi Enkovaara

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Tags: Computer science, Intel Xeon Phi, Python

December 1, 2014 by hgpu

A Framework for Composing High-Performance OpenCL from Python Descriptions

Michael Anderson

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 480, OpenCL, Optical flow, Python, Thesis

November 29, 2014 by hgpu

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

Guray Ozen

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Tesla M2090, Thesis

November 29, 2014 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Real-Time Hair Rendering

SiftCU: An Accelerated Cuda Based Implementation of SIFT

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

GPU accelerated feature algorithms for mobile devices

An Open-Source GPU-Accelerated Feature Extraction Tool

GPU Declarative Framework

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

pyMIC: A Python Offload Module for the Intel Xeon Phi Coprocessor

A Framework for Composing High-Performance OpenCL from Python Descriptions

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

Recent source codes

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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