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A Framework for Automatic OpenMP Code Generation

A. Raghesh

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Tags: Code generation, Computer science, OpenCL, Optimization, Programming techniques, Thesis

October 7, 2011 by hgpu

Run-time Reconfigurable Multiprocessors

Madhura Purnaprajna

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Tags: ATI, Computer science, FPGA, Hardware Architecture, nVidia, Performance, Thesis

October 7, 2011 by hgpu

CUDA performance analyzer

Aniruddha Dasgupta

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Tags: Analytical model, Computer science, CUDA, Fast multipole method, nVidia, Optimization, Performance, Tesla C1060, Thesis

October 6, 2011 by hgpu

Parallelisation of Java for Graphics Processors

Peter Calvert

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Package, Thesis

October 6, 2011 by hgpu

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Olav Aanes Fagerlund

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 280, OpenCL, Thesis

October 6, 2011 by hgpu

Berkeley Dwarfs on CUDA

Paul Springer

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Thesis

October 4, 2011 by hgpu

Power Management and Optimization

Hari Sundararajan

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Tags: Computer science, CUDA, Energy-efficient computing, Green, nVidia, nVidia GeForce GTX 260, Performance, Thesis

October 2, 2011 by hgpu

An Execution Model and Runtime For Heterogeneous Many-Core Systems

Gregory Diamos

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Package, PTX, Tesla C1060, Tesla S870, Thesis

October 2, 2011 by hgpu

Power-Efficient Accelerators for High-Performance Applications

Ganesh Suryanarayan Dasika

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Tags: Computer science, Energy-efficient computing, Performance, Thesis

October 2, 2011 by hgpu

Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems

Mayank Daga

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Heterogeneous systems, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050, Thesis

September 30, 2011 by hgpu

A PTX Code Generator for LLVM

Helge Rhodin

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Optimization, PTX, Thesis, Virtualization

September 30, 2011 by hgpu

Adding special-purpose processor support to the Erlang VM

Christofer Ferm

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Tags: Computer science, DSP, nVidia, nVidia GeForce 9400 M, OpenCL, Performance, Thesis, Virtualization

September 30, 2011 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

A Framework for Automatic OpenMP Code Generation

Run-time Reconfigurable Multiprocessors

CUDA performance analyzer

Parallelisation of Java for Graphics Processors

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Berkeley Dwarfs on CUDA

Power Management and Optimization

An Execution Model and Runtime For Heterogeneous Many-Core Systems

Power-Efficient Accelerators for High-Performance Applications

Architecture-Aware Mapping and Optimization on Heterogeneous Computing Systems

A PTX Code Generator for LLVM

Adding special-purpose processor support to the Erlang VM

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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