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OpenCL Library for Parallel Graph Search Algorithms

Christian Fischer

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, OpenCL, Path problems, Thesis

July 25, 2017 by hgpu

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

Francesc Sastre Cabot

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, Tesla K80, Tesla M2090, Thesis

July 22, 2017 by hgpu

Automatically Selecting Profitable Thread Block Sizes Using Machine Learning

Tiffany A. Connors

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Tags: Computer science, CUDA, Machine learning, nVidia, Performance, Tesla K40, Thesis

July 22, 2017 by hgpu

Fine-Grain Acceleration of Graph Algorithms on a Heterogeneous Chip

Cagri Eryilmaz

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Tags: Algorithms, APU, Computer science, Graph theory, Heterogeneous systems, OpenCL, Thesis

July 19, 2017 by hgpu

Synthesis of Embedded Software using Dataflow Schedule Graphs

Abhay Raina

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Tags: Computer science, DSP, nVidia, nVidia GeForce GTX 680, OpenCL, Signal processing, Thesis

July 2, 2017 by hgpu

An Analysis of Variation Between Cores For Intel Xeon Phi Knights Corner And Xeon Phi Knights Landing

Jamar Robinson

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

June 25, 2017 by hgpu

UT-OCL: An OpenCL Framework for Embedded Systems Using Xilinx FPGAs

Vincent Mirian

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, SoC, Thesis

June 5, 2017 by hgpu

Program Acceleration in a Heterogeneous Computing Environment Using OpenCL, FPGA, and CPU

Herman Noel Hoffman

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, SoC, Thesis

June 5, 2017 by hgpu

SparkJNI: A Reference Design for a Heterogeneous Apache Spark Framework

Tudor Alexandru Voicu

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Tags: big data, Computer science, FPGA, Heterogeneous systems, Hybrid computing, Java, OpenCL, Spark, Thesis

June 1, 2017 by hgpu

Implementing Efficient, Portable Computations for Machine Learning

Matthew Walter Moskewicz

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Tags: Algorithms, AMD R9 Nano, ATI, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

May 24, 2017 by hgpu

GPUMap: A Transparently GPU-Accelerated Map Function

Ivan Pachev

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Tags: Computer science, CUDA, Distributed computing, Java, MapReduce, nVidia, nVidia GeForce GTX 980, Python, Thesis

May 22, 2017 by hgpu

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Konstantinos Krommydas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Performance, Tesla K20, Thesis

May 9, 2017 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

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

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high performance computing on graphics processing units: hgpu.org

Theses

OpenCL Library for Parallel Graph Search Algorithms

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

Automatically Selecting Profitable Thread Block Sizes Using Machine Learning

Fine-Grain Acceleration of Graph Algorithms on a Heterogeneous Chip

Synthesis of Embedded Software using Dataflow Schedule Graphs

An Analysis of Variation Between Cores For Intel Xeon Phi Knights Corner And Xeon Phi Knights Landing

UT-OCL: An OpenCL Framework for Embedded Systems Using Xilinx FPGAs

Program Acceleration in a Heterogeneous Computing Environment Using OpenCL, FPGA, and CPU

SparkJNI: A Reference Design for a Heterogeneous Apache Spark Framework

Implementing Efficient, Portable Computations for Machine Learning

GPUMap: A Transparently GPU-Accelerated Map Function

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Recent source codes

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

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

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