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hgpu.org » Heterogeneous systems

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

Qingyu Meng, Alan Humphrey, Martin Berzins

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, MPI, nVidia, nVidia GeForce GTX 570, Task scheduling, Tesla C2070

November 24, 2012 by hgpu

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Thomas R. W. Scogland, Wu-chun Feng, Barry Rountree, Bronis R. de Supinski

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C2070

November 22, 2012 by hgpu

Automatic generation of software pipelines for heterogeneous parallel systems

Jacques A. Pienaar, Srimat Chakradhar, Anand Raghunathan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C1060

November 22, 2012 by hgpu

ValuePack: value-based scheduling framework for CPU-GPU clusters

Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Tesla C2050

November 21, 2012 by hgpu

Pattern Recognition with OpenCL Heterogeneous Platform

Jordan Vrtanoski, Toni Draganov Stojanovski

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, Neural networks, OpenCL, Pattern recognition

November 21, 2012 by hgpu

Accelerating MapReduce on a coupled CPU-GPU architecture

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: APU, ATI, ATI Radeon HD 6550, Computer science, Data mining, Heterogeneous systems, Machine learning, MapReduce, OpenCL

November 20, 2012 by hgpu

High locality and increased intra-node parallelism for solving finite element models on GPUs by novel element-by-element implementation

Imre Kiss, Zsolt Badics, Szabolcs Gyimothy, Jozsef Pavo

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Tags: Computer science, CUDA, FEM, Finite element method, Heterogeneous systems, nVidia, nVidia GeForce GTX 590

November 18, 2012 by hgpu

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Mayank Daga, Mark Nutter

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Tags: APU, ATI, ATI Radeon HD 7660, ATI Radeon HD 7970, Computer science, Databases, Heterogeneous systems, OpenCL

November 18, 2012 by hgpu

Parallel implementations of the MinMin heterogeneous computing scheduler in GPU

Mauro Canabe, Sergio Nesmachnow

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C1060

November 16, 2012 by hgpu

CUDA and OpenCL Implementations of 3D CT Reconstruction for Biomedical Imaging

Saoni Mukherjee, Nicholas Moore, James Brock, Miriam Leeser

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Tags: ATI, ATI Radeon HD 5870, Computed tomography, CT, CUDA, Heterogeneous systems, Image reconstruction, Medicine, nVidia, OpenCL, Tesla C2070

November 16, 2012 by hgpu

Device specialization in heterogeneous multi-GPU environments

Gabriele Cocco, Antonio Cisternino

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Tags: AMD Fusion, ATI, ATI IL, ATI Radeon HD 5870, Computer science, GPU cluster, Heterogeneous systems, Task scheduling

November 15, 2012 by hgpu

Reusable OpenCL FPGA Infrastructure

Stephen Alexander Chin

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Thesis

November 8, 2012 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

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Automatic generation of software pipelines for heterogeneous parallel systems

Pattern Recognition with OpenCL Heterogeneous Platform

Accelerating MapReduce on a coupled CPU-GPU architecture

High locality and increased intra-node parallelism for solving finite element models on GPUs by novel element-by-element implementation

Exploiting Coarse-grained Parallelism in B+ Tree Searches on an APU

Parallel implementations of the MinMin heterogeneous computing scheduler in GPU

CUDA and OpenCL Implementations of 3D CT Reconstruction for Biomedical Imaging

Device specialization in heterogeneous multi-GPU environments

Reusable OpenCL FPGA Infrastructure

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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