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Hybrid algorithms for efficient Cholesky decomposition and matrix inverse using multicore CPUs with GPU accelerators

Gary Macindoe

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, Machine learning, Matrix decomposition, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 285, Tesla S1070, Thesis

January 29, 2014 by hgpu

Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

Jing Zhang, Hao Wang, Heshan Lin, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Task scheduling

January 29, 2014 by hgpu

On the Programmability and Performance of Heterogeneous Platforms

Konstantinos Krommydas, Thomas R.W. Scogland, Wu-chun Feng

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Tags: Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, N-body simulation, nVidia, OpenACC, Optimization, Tesla K20

January 29, 2014 by hgpu

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

Ashis Kumar Dash

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Quadro FX 3700

January 29, 2014 by hgpu

Impact of communication times on mixed CPU/GPU applications scheduling using KAAPI

David Beniamine

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Tags: Computer science, CUDA, nVidia, nVidia Quadro NVS 300, Task scheduling, Tesla C2050, Thesis

January 29, 2014 by hgpu

Scheduling on Manycore and Heterogeneous Graphics Processors

Stanley Tzeng

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL, Thesis

January 28, 2014 by hgpu

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications

Bo Fang, Karthik Pattabiraman, Matei Ripeanu, Sudhanva Gurumurthi

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Tags: Computer science, CUDA, GPGPU-sim, nVidia

January 28, 2014 by hgpu

Performance-Correctness Challenges in Emerging Heterogeneous Multicore Processors

Vineeth Thamarassery Mekkat

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce 8600 GTS, Thesis

January 28, 2014 by hgpu

gem5-gpu: A Heterogeneous CPU-GPU Simulator

Jason Power, Joel Hestness, Marc S. Orr, Mark D. Hill, David A. Wood

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Tags: Computer science, CUDA, GPGPU-sim, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

January 26, 2014 by hgpu

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Marcel Koster, Roland Leissa, and Sebastian Hack, Richard Membarth, Philipp Slusallek

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

January 26, 2014 by hgpu

Computing Best Possible Pseudo-Solutions to Interval Linear Systems of Equations

Anatoly V. Panyukov, Valentin A. Golodov

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Tags: Computer science, CUDA, Linear Algebra, MPI, nVidia, nVidia GeForce GTX 460

January 26, 2014 by hgpu

Low-latency Image Recognition with GPU-accelerated Convolutional Networks for Web-based Services

Fu Jie Huang

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Tags: Cloud, CUDA, Image processing, Image recognition, nVidia, nVidia GeForce GTX 560 Ti, Thesis

January 26, 2014 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Hybrid algorithms for efficient Cholesky decomposition and matrix inverse using multicore CPUs with GPU accelerators

Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

On the Programmability and Performance of Heterogeneous Platforms

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

Impact of communication times on mixed CPU/GPU applications scheduling using KAAPI

Scheduling on Manycore and Heterogeneous Graphics Processors

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications

Performance-Correctness Challenges in Emerging Heterogeneous Multicore Processors

gem5-gpu: A Heterogeneous CPU-GPU Simulator

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Computing Best Possible Pseudo-Solutions to Interval Linear Systems of Equations

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

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

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