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An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Nam-Luc Tran, Sabri Skhiri, Arnaud Schils, Edgar Isaac Hiroshi Leon Saiki

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan, Package

December 2, 2014 by hgpu

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Chih-Sheng Lin

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 690, OpenCL, Task scheduling, Tesla C2050, Thesis

December 1, 2014 by hgpu

Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures

E. Bajrovic, S. Benkner

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Tags: Computer science, Heterogeneous systems, nVidia, OpenCL, OpenCV, Performance, Tesla C2050, Tesla K20

November 20, 2014 by hgpu

Hybrid CPU-GPU Pipeline Framework

Fahad Khalid, Frank Feinbube, Andreas Polze

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Tags: Biology, Computational biology, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 680

November 18, 2014 by hgpu

Semi-Analytic Solutions to the Radiative Transfer Equations via Hetergeneous Computing

Daniel Alphin Holladay

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Tags: Astrophysics, Heterogeneous systems, nVidia, OpenCL, Physics, Tesla C2050, Tesla C2075, Thesis

November 13, 2014 by hgpu

Bounds on the Energy Consumption of Computational Kernels

Andrew Gearhart

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, Package, Tesla K20, Thesis

November 3, 2014 by hgpu

Using an OpenCL Framework to Evaluate Interconnect Implementations on FPGAs

Vincent Mirian, Paul Chow

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL

October 31, 2014 by hgpu

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Lokendra Singh Panwar

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computational Complexity, Computer science, CUDA, Finite difference, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Seismology, Tesla C1060, Tesla C2050, Thesis

October 29, 2014 by hgpu

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

David Markvica

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Tags: Algorithms, Biology, Computational biology, Computer science, Heterogeneous systems, Metaheuristics, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Optimization, Pattern recognition, Thesis

October 27, 2014 by hgpu

Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases

Piotr Przymus

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Tags: Algorithms, Compression, Computer science, CUDA, Data mining, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, Tesla C2070, Tesla M2070, Thesis

October 24, 2014 by hgpu

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

Jing Wu

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Tags: Computer science, CUDA, FFT, Heterogeneous systems, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Poisson equation, Tesla C1060, Tesla C2050, Thesis

October 22, 2014 by hgpu

Heterogeneous computing with an algorithmic skeleton framework

Fabio Miguel Cardoso Soldado

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, Heterogeneous systems, OpenCL, Programming techniques, Thesis

October 20, 2014 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

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures

Hybrid CPU-GPU Pipeline Framework

Semi-Analytic Solutions to the Radiative Transfer Equations via Hetergeneous Computing

Bounds on the Energy Consumption of Computational Kernels

Using an OpenCL Framework to Evaluate Interconnect Implementations on FPGAs

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

Heterogeneous computing with an algorithmic skeleton framework

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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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