high performance computing on graphics processing units: hgpu.org

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A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Koushik Mandal

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2075, Thesis

July 23, 2014 by hgpu

A Multi-GPU Compute Solution for Optimized Genomic Selection Analysis

Trevor DeVore

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Tags: Bayesian, Bioinformatics, Biology, CUDA, Heterogeneous systems, nVidia, Tesla K20, Tesla K40, Thesis

July 23, 2014 by hgpu

High Performance Low Power Embedded Vision Systems

Antonis S. Nikitakis

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Tags: Algorithms, ARM, Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, OpenCV, Thesis

July 22, 2014 by hgpu

Performance-efficient mechanisms for managing irregularity in throughput processors

Minsoo Rhu

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Prefetch, Thesis

July 20, 2014 by hgpu

Algorithms for Large-Scale Power Delivery Network Analysis on Massively Parallel Architectures

Konstantis Daloukas

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Tags: Algorithms, Computer science, CUDA, nVidia, Power Systems Simulation, Tesla K20, Thesis

July 20, 2014 by hgpu

Water simulation for cell based sandbox games

Christian Lundell

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Tags: Algorithms, Fluid dynamics, Fluid simulation, Games, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 670, OpenGL, Thesis

July 20, 2014 by hgpu

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

Dariusz Cieslakiewicz

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 660 M, Thesis

July 18, 2014 by hgpu

Implementation & Parallelisation of FDTD code for Electromagnetic Scattering

Deshpande Varadendra Ravindra

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Tags: Algorithms, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, MPI, nVidia, OpenMPI, Tesla C2070, Thesis

July 18, 2014 by hgpu

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Csaba Nemes

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 570, Tesla K20, Thesis

July 17, 2014 by hgpu

Computational Simulation of Freely Falling Water Droplets on Graphics Processing Units

Jeremy Appleyard

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Tags: CUDA, Fluid dynamics, nVidia, Tesla C1060, Tesla S2050, Thesis

July 15, 2014 by hgpu

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

David Rohr

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Review, Thesis

July 14, 2014 by hgpu

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 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

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high performance computing on graphics processing units: hgpu.org

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

A Multi-GPU Compute Solution for Optimized Genomic Selection Analysis

High Performance Low Power Embedded Vision Systems

Performance-efficient mechanisms for managing irregularity in throughput processors

Algorithms for Large-Scale Power Delivery Network Analysis on Massively Parallel Architectures

Water simulation for cell based sandbox games

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

Implementation & Parallelisation of FDTD code for Electromagnetic Scattering

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Computational Simulation of Freely Falling Water Droplets on Graphics Processing Units

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

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

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