high performance computing on graphics processing units: hgpu.org

hgpu.org » Thesis

Machine Learning from Streaming Data in Heterogeneous Computing Environments

Yusuf Guven Toprakkiran

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Thesis

April 11, 2017 by hgpu

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Maria Barreda Vaya

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OmpSs, Tesla C2050, Thesis

April 11, 2017 by hgpu

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Julian Romera

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenMPI, Performance, Tesla K80, Tesla M2090, Thesis

April 7, 2017 by hgpu

Pipelined MapReduce: A Decoupled MapReduce RunTime for Shared Memory Multi-Processors

Konstantinos Iliakis

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Tags: Computer science, Intel Xeon Phi, MapReduce, Thesis

March 28, 2017 by hgpu

Energy conservation techniques for GPU computing

Xinxin Mei

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 780, nVidia GeForce GTX 980, Task scheduling, Thesis

March 28, 2017 by hgpu

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

Andrew J. Younge

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Tags: Cloud, Computer science, CUDA, Distributed computing, Molecular dynamics, nVidia, OpenCL, Tesla C2075, Tesla K20, Thesis, Virtualization

March 9, 2017 by hgpu

Is GPGPU CCL worth it? A performance comparison between some GPU and CPU algorithms for solving connected components labeling on binary images

Alex Sundstrom, Victor Ahdel

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Tags: Algorithms, AMD Radeon R9 280X, ATI, Computer science, Image processing, nVidia, nVidia GeForce GTX 960, OpenCL, Performance, Thesis

February 26, 2017 by hgpu

A Dynamic Programming Model To Solve Optimisation Problems Using GPUs

Jonathan Francis O'Connell

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 960, nVidia GeForce GTX Titan, Optimisation, Thesis

February 7, 2017 by hgpu

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Yuan Yuan

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Thesis

February 7, 2017 by hgpu

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

Robert T. Kelly

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Tags: Computer science, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, Theano, Thesis, Torch

February 5, 2017 by hgpu

Fast Fourier Transforms over Prime Fields of Large Characteristic and their Implementation on Graphics Processing Units

Davood Mohajerani

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 760 M, Security, Thesis

February 5, 2017 by hgpu

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

Felipe Sulser Larraz

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Tags: Benchmarking, Bioinformatics, Biology, Computer science, Databases, Filtering, Intel Xeon Phi, Sequence alignment, Smith-Waterman algorithm, Thesis

February 2, 2017 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Machine Learning from Streaming Data in Heterogeneous Computing Environments

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Pipelined MapReduce: A Decoupled MapReduce RunTime for Shared Memory Multi-Processors

Energy conservation techniques for GPU computing

Is GPGPU CCL worth it? A performance comparison between some GPU and CPU algorithms for solving connected components labeling on binary images

A Dynamic Programming Model To Solve Optimisation Problems Using GPUs

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

Fast Fourier Transforms over Prime Fields of Large Characteristic and their Implementation on Graphics Processing Units

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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