high performance computing on graphics processing units: hgpu.org

hgpu.org » Thesis

Jit4OpenCL: a compiler from Python to OpenCL

Xunhao Li

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Tags: ATI, ATI Radeon HD 5850, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, OpenCL, Python, Thesis

October 29, 2011 by hgpu

Using OpenCL for image analysis

Niklas Frisk

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Tags: Algorithms, Benchmarking, Image processing, Java, nVidia, nVidia GeForce 8600 M, OpenCL, Thesis

October 29, 2011 by hgpu

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 2011 by hgpu

Compiling Stream Applications for Heterogeneous Architectures

Amir H. Hormati

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Tags: Compilers, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Optimization, Tesla C2050, Thesis

October 28, 2011 by hgpu

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Giovanni Ansaloni

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Tags: Algorithms, Computer science, Design space exploration, Heterogeneous systems, Thesis

October 28, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Techniques to maximize memory bandwidth on the Rigel compute accelerator

William J. Tuohy

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Tags: ATI, ATI Radeon HD 5870, Computer science, Memory, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10, Thesis

October 27, 2011 by hgpu

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Robert Hegner

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package, Thesis

October 27, 2011 by hgpu

The Model of Computation of CUDA and its Formal Semantics

Axel Habermaier

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 480, PTX, Thesis

October 25, 2011 by hgpu

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Pablo Lamilla Alvarez

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Tags: Computer science, GPU cluster, nVidia, nVidia GeForce GT 220, OpenCL, Performance, Thesis

October 24, 2011 by hgpu

Design and Implementation of Centrally-Coordinated Peer-to-Peer Live-streaming

Roberto Roverso

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Tags: Algorithms, Computer science, Consensus, CUDA, Network communications, Networks, nVidia, nVidia GeForce GTX 295, Optimization, Thesis

October 23, 2011 by hgpu

Power and Performance Studies of the Explicit Multi-Threading (XMT) Architecture

Fuat Keceli

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Tags: Algorithms, ASIC, Benchmarking, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Package, Performance, Thesis

October 23, 2011 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

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

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

See all packages

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high performance computing on graphics processing units: hgpu.org

Jit4OpenCL: a compiler from Python to OpenCL

Using OpenCL for image analysis

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Compiling Stream Applications for Heterogeneous Architectures

Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Matrix inversion speed up with CUDA

Techniques to maximize memory bandwidth on the Rigel compute accelerator

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

The Model of Computation of CUDA and its Formal Semantics

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Design and Implementation of Centrally-Coordinated Peer-to-Peer Live-streaming

Power and Performance Studies of the Explicit Multi-Threading (XMT) Architecture

Recent source codes

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

Data-efficient LLM Fine-tuning for Code Generation

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

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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