high performance computing on graphics processing units: hgpu.org

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Programming issues for video analysis on Graphics Processing Units

Juan Gomez Luna

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Signal processing, Thesis

April 12, 2012 by hgpu

A Study of Productivity and Performance of Modern Vector Processors

Paul Springer

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 6000, OpenCL, Performance, Thesis

April 9, 2012 by hgpu

Robust Computational Tools for Multiple Testing With Genetic Association Studies

William L. Welbourn Jr.

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Thesis

April 7, 2012 by hgpu

OpenCL framework for a CPU, GPU, and FPGA Platform

Taneem Ahmed

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Tags: ATI, ATI Radeon HD 5450, Computer science, FPGA, Heterogeneous systems, OpenCL, Thesis

April 6, 2012 by hgpu

On the Cryptanalysis of Public-Key Cryptography

Joppe Willem Bos

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Tags: Computer science, CUDA, Elliptic curves, Factorization, Modular arithmetic, nVidia, Playstation, Security, Thesis

April 2, 2012 by hgpu

Distributed Password Cracking Platform

Gerrie Veerman, Dimitar Pavlov

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Tags: Computer science, MPI, Review, Security, Thesis

March 31, 2012 by hgpu

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

Cedric Augonnet

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Tags: Cell processor, Computer science, CUDA, Databases, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Task scheduling, Tesla C2050, Tesla M2070, Tesla S1070, Thesis

March 29, 2012 by hgpu

A computing origami: Optimized code generation for emerging parallel platforms

Hagiescu Miriste Andrei Mihai

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Tags: Code generation, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 8800 GTX, Optimization, Tesla S1070, Thesis

March 29, 2012 by hgpu

Accelerating the FDTD Method Using SSE and Graphics Processing Units

Matthew J. Livesey

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Tags: Computer science, CUDA, Data parallelism, FDTD, Finite-difference time-domain, nVidia, Tesla M2050, Tesla T10, Thesis

March 28, 2012 by hgpu

Accelerating Constraint Automata Composition with GPGPU Parallelization

Gunnar K. Vilbergsson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Thesis

March 27, 2012 by hgpu

Dynamic Translation of Runtime Environments for Heterogeneous Computing

Rodrigo Dominguez

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Design space exploration, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Thesis

March 27, 2012 by hgpu

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Dimitar Lukarski

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FEM, Finite difference, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla M1060, Tesla S1070, Thesis

March 16, 2012 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming issues for video analysis on Graphics Processing Units

A Study of Productivity and Performance of Modern Vector Processors

Robust Computational Tools for Multiple Testing With Genetic Association Studies

OpenCL framework for a CPU, GPU, and FPGA Platform

On the Cryptanalysis of Public-Key Cryptography

Distributed Password Cracking Platform

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

A computing origami: Optimized code generation for emerging parallel platforms

Accelerating the FDTD Method Using SSE and Graphics Processing Units

Accelerating Constraint Automata Composition with GPGPU Parallelization

Dynamic Translation of Runtime Environments for Heterogeneous Computing

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Recent source codes

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

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

Most viewed papers (last 30 days)