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Heterogeneous Clustering with Homogeneous Code: Accelerate MPI Applications Without Code Surgery Using Intel Xeon Phi Coprocessors

Andrey Vladimirov and Vadim Karpusenko

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Tags: Heterogeneous systems, Intel Phi, Intel Xeon Phi, Monte Carlo simulation, MPI, Portability, Task scheduling

October 18, 2013 by Andrey Vladimirov

Dynamic Load Balancing in GPU-Based Systems – Early Experiments

Alvaro Luiz Fazenda, Celso L. Mendes, Laxmikant V. Kale, Jairo Panetta, Eduardo Rocha Rodrigues

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Tags: Computer science, CUDA, nVidia, OpenACC, Task scheduling, Tesla K20, Virtualization

October 18, 2013 by hgpu

OpenCL Task Partitioning in the Presence of GPU Contention

Dominik Grewe, Zheng Wang, and Michael F.P. O'Boyle

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Tags: Computer science, Heterogeneous systems, Intel, Intel HD Graphics 4000, Machine learning, OpenCL, Task scheduling

September 25, 2013 by hgpu

A Feedback Approach to Task Partitioning in Heterogeneous Architectures

Yasir Ali, Zuhair Qadir

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Tags: ATI, ATI Radeon HD 5770, Computer science, Heterogeneous systems, OpenCL, Task scheduling

August 30, 2013 by hgpu

Exploiting the Parallelism of Heterogeneous Systems using Dataflow Graphs on Top of OpenCL

Lars Schor, Andreas Tretter, Tobias Scherer, Lothar Thiele

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Tags: ATI, ATI Radeon HD 7750, Computer science, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 670, nVidia Quadro K 2000 M, OpenCL, Task scheduling

August 13, 2013 by hgpu

Opportunities for Heterogeneous CPUGPU Task Scheduling

Christiaan Arnoldus, Robert Witte

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Tags: ATI, ATI Radeon HD 4850, Computer science, Heterogeneous systems, nVidia, nVidia GeForce 9200 M GS, OpenCL, Task scheduling

July 31, 2013 by hgpu

Scheduling by Work-Stealing in Hybrid Parallel Architectures

Vinicius Garcia Pinto, Nicolas Maillard

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Task scheduling

July 24, 2013 by hgpu

Parallelization the Job-shop Problem on Distributed and Shared Memory Architectures

Vu Dinh Trung, Tran Van Lang

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 250, Task scheduling

July 17, 2013 by hgpu

Hybrid Scheduling for Event-driven Simulation over Heterogeneous Computers

Bilel Ben Romdhanne, Mohamed Said Mosli, Navid Nikaein, Christian Bonnet

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, Task scheduling

July 9, 2013 by hgpu

Towards Performance-Portable, Scalable, and Convenient Linear Algebra

Philippe Tillet, Karl Rupp, Siegfried Selberherr, Chin-Teng Lin

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Tags: ATI, ATI Radeon HD 7970, Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 470, OpenCL, Task scheduling

July 1, 2013 by hgpu

Parallel Asynchronous Modelization and Execution of Cholesky Algorithm using Petri Nets

Gustavo Wolfmann, Armando De Giusti

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 470, Task scheduling

June 19, 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

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Heterogeneous Clustering with Homogeneous Code: Accelerate MPI Applications Without Code Surgery Using Intel Xeon Phi Coprocessors

Dynamic Load Balancing in GPU-Based Systems – Early Experiments

OpenCL Task Partitioning in the Presence of GPU Contention

A Feedback Approach to Task Partitioning in Heterogeneous Architectures

Exploiting the Parallelism of Heterogeneous Systems using Dataflow Graphs on Top of OpenCL

Opportunities for Heterogeneous CPUGPU Task Scheduling

Scheduling by Work-Stealing in Hybrid Parallel Architectures

Parallelization the Job-shop Problem on Distributed and Shared Memory Architectures

Hybrid Scheduling for Event-driven Simulation over Heterogeneous Computers

Towards Performance-Portable, Scalable, and Convenient Linear Algebra

Parallel Asynchronous Modelization and Execution of Cholesky Algorithm using Petri Nets

Task scheduling in hybrid CPU-GPU systems

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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