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Prius: A Runtime for Hybrid Computing

Dominik Grewe

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Tags: Computer science, Heterogeneous systems, Hybrid computing, OpenCL

March 15, 2013 by hgpu

Selection of Task Implementations in the Nanos++ Runtime

Judit Planas, Rosa M. Badia, Eduard Ayguade, Jesus Labarta

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla M2090

March 14, 2013 by hgpu

A Scalable Heterogeneous Parallelization Framework for Iterative Local Searches

Martin Burtscher, Hassan Rabeti

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Search, Tesla M2090

March 12, 2013 by hgpu

Accelerating Simulation of Agent-Based Models on Heterogeneous Architectures

Jin Wangy, Norman Rubinz, Haicheng Wuy, Sudhakar Yalamanchiliy

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Tags: Algorithms, ATI, ATI Radeon HD 7660, ATI Radeon HD 7950, Computer science, Heterogeneous systems, OpenCL, Performance, Vehicular traffic

March 5, 2013 by hgpu

An efficient scheduling scheme using estimated execution time for heterogeneous computing systems

Hong Jun Choi, Dong Oh Son, Seung Gu Kang, Jong Myon Kim, Hsien-Hsin Lee, Cheol Hong Kim

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8500 GT

February 22, 2013 by hgpu

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

Kyungjoo Kim

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Tags: Computer science, CUDA, Factorization, FEM, Finite element method, Heterogeneous systems, nVidia, Package, Sparse direct solvers, Task scheduling, Tesla M2070

February 21, 2013 by hgpu

An abstract object oriented runtime system for heterogeneous parallel architecture

Jean-Marc Gratien

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2070, Tesla T10

February 20, 2013 by hgpu

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Chris J. Newburn, Rajiv Deodhar, Serguei Dmitriev, Ravi Murty, Ravi Narayanaswamy, John Wiegert, Francisco Chinchilla, Russell McGuire

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Tags: Compilers, Computer science, Heterogeneous systems, Intel, Intel Phi, Programming techniques

February 18, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Sidi Ahmed Mahmoudi, Pierre Manneback

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 280, Pattern recognition, Tesla C1060

February 14, 2013 by hgpu

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Stephen Won

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Tags: Computer vision, CUDA, Data mining, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, SIFT, Signal processing, Thesis

February 12, 2013 by hgpu

Adaptation of the MapReduce programming framework to compute-intensive data-analytics kernels

Reza Farivar

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 275, Thesis

February 9, 2013 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Prius: A Runtime for Hybrid Computing

Selection of Task Implementations in the Nanos++ Runtime

A Scalable Heterogeneous Parallelization Framework for Iterative Local Searches

Accelerating Simulation of Agent-Based Models on Heterogeneous Architectures

An efficient scheduling scheme using estimated execution time for heterogeneous computing systems

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

An abstract object oriented runtime system for heterogeneous parallel architecture

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Adaptation of the MapReduce programming framework to compute-intensive data-analytics kernels

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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