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hgpu.org » Heterogeneous systems

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Roshan Dathathri, Chandan Reddy, Thejas Ramashekar, Uday Bondhugula

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Tags: ATI, ATI FirePro V4800, ATI Radeon HD 6550, Code generation, Computer science, Heterogeneous systems, nVidia, Tesla C2050

July 1, 2013 by hgpu

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

Ana Balevic

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Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla C2050, Thesis

July 1, 2013 by hgpu

HadoopCL: MapReduce on Distributed Heterogeneous Platforms Through Seamless Integration of Hadoop and OpenCL

Max Grossman, Mauricio Breternitz, Vivek Sarkar

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Tags: APU, ATI, Computer science, Heterogeneous systems, Java, MapReduce, nVidia, OpenCL, Tesla M2050

June 30, 2013 by hgpu

A model of dynamic compilation for heterogeneous compute platforms

Andrew Kerr

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenCL, PTX, Thesis

June 29, 2013 by hgpu

Delaunay Triangulation in R3 on the GPU

Ashwin Nanjappa

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Package, Thesis, Voronoi diagram

June 18, 2013 by hgpu

Accelerating GPU Programs by Reducing Irregular Control Flow and Memory Access

Tomohiro Okuyama

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Tags: Algorithms, Biophysics, CUDA, Differential equations, Heterogeneous systems, nVidia, ODEs, Ordinary differential equations, Physics, Tesla C2070, Thesis

June 18, 2013 by hgpu

Auto-Tunning of Data Communication on Heterogeneous Systems

Marc Jorda, Ivan Tanasic, Javier Cabezas, Lluis Vilanova, Isaac Gelado, Nacho Navarro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C2050, Tesla C2070, Tesla M2090

June 17, 2013 by hgpu

An Analysis of Conventional and Heterogeneous Workloads on Production Supercomputing Resources

Jonathan Allen Berkhahn

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Tags: Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla M2050, Tesla S2050

June 13, 2013 by hgpu

A MapReduce Framework for Heterogeneous Computing Architectures

Marwa Khamis Elteir

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, OpenCL, Tesla C2050, Tesla M2050, Thesis

June 6, 2013 by hgpu

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Rafael Alejandro Vejarano, Phuong Thi Yen, Jeong-Gun Lee

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Tags: Computer science, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 460, OpenCL, Performance

June 4, 2013 by hgpu

Task scheduling in hybrid CPU-GPU systems

Martin Krulis, Zbynek Falt, David Bednarek, Jakub Yaghob

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Operating systems, Task scheduling, Tesla M2090

June 2, 2013 by hgpu

From Experiment to Design – Fault Characterization and Detection in Parallel Computer Systems Using Computational Accelerators

Keun Soo Yim

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Tags: Computer science, CUDA, Fault tolerance, Heterogeneous systems, MPI, nVidia, Tesla S1070, Thesis

May 30, 2013 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

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high performance computing on graphics processing units: hgpu.org

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

HadoopCL: MapReduce on Distributed Heterogeneous Platforms Through Seamless Integration of Hadoop and OpenCL

A model of dynamic compilation for heterogeneous compute platforms

Delaunay Triangulation in R3 on the GPU

Accelerating GPU Programs by Reducing Irregular Control Flow and Memory Access

Auto-Tunning of Data Communication on Heterogeneous Systems

A MapReduce Framework for Heterogeneous Computing Architectures

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Task scheduling in hybrid CPU-GPU systems

From Experiment to Design – Fault Characterization and Detection in Parallel Computer Systems Using Computational Accelerators

Recent source codes

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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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