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Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Matthew Sellitto

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Tags: Algorithms, Heterogeneous systems, Image processing, nVidia, OpenCL, Optimization, Sensing, Tesla M2070, Thesis

May 30, 2012 by hgpu

Compiler optimizations for directive-based programming for accelerators

Matias Piispanen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Optimization

May 24, 2012 by hgpu

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Siegfried Benkner, Enes Bajrovic, Erich Marth, Martin Sandrieser, Raymond Namyst, Samuel Thibault

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

May 20, 2012 by hgpu

Automatic Implementation of Evolutionary Algorithms on GPUs using ESDL

Steve Dower

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Tags: Algorithms, Computer science, Evolutionary Computations, Heterogeneous systems, nVidia, nVidia GeForce GT 540 M

May 19, 2012 by hgpu

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

VCV.Rao, Nisha Agrawa, Samrit Maity

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Tags: AMD FirePro V5900, AMD FirePro V7900, AMD FireStream 9350, ATI, Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, OpenCL, Partial differential equations, PDEs, Tesla C2060

May 19, 2012 by hgpu

Programming and Scheduling Model for Supporting Heterogeneous Accelerators in Linux

Tobias Beisel, Tobias Wiersema, Christian Plessl, Andre Brinkmann

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package, Task scheduling

May 19, 2012 by hgpu

A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix Multiply

Paolo D'Alberto

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 6750, Computer science, Heterogeneous systems, Mathematical Software, Matrix multiplication, OpenCL

May 16, 2012 by hgpu

Mapping a Data-Flow Programming Model onto Heterogeneous Platforms

Alina Sbirlea, Yi Zou, Zoran Budimlic, Jason Cong, Vivek Sarkar

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Tags: Algorithms, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Programming techniques, Tesla C1060

May 14, 2012 by hgpu

Heterogeneous Computing in Economics: a Simplified Approach

Matt P. Dziubinski, Stefano Grassi

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Tags: CUDA, Data parallelism, Finance, Heterogeneous systems, nVidia, nVidia GeForce GT 520 M, nVidia GeForce GTS 450, Optimization

May 14, 2012 by hgpu

Scalable Distributed Fast Multipole Methods

Qi Hu, Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla C2050

May 12, 2012 by hgpu

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Alan Humphrey, Qingyu Meng, Martin Berzins, Todd Harman

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Tags: CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, MPI, nVidia, Partial differential equations, Pthreads, Task scheduling, Tesla M2090

May 11, 2012 by hgpu

Large scale parallel state space search utilizing graphics processing units and solid state disks

Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Probabilistic model checking, Search strategies, Thesis

May 11, 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

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high performance computing on graphics processing units: hgpu.org

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Compiler optimizations for directive-based programming for accelerators

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Automatic Implementation of Evolutionary Algorithms on GPUs using ESDL

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

Programming and Scheduling Model for Supporting Heterogeneous Accelerators in Linux

A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix Multiply

Mapping a Data-Flow Programming Model onto Heterogeneous Platforms

Heterogeneous Computing in Economics: a Simplified Approach

Scalable Distributed Fast Multipole Methods

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Large scale parallel state space search utilizing graphics processing units and solid state disks

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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