Matrix multiplication | Page 12

hgpu.org » Matrix multiplication

Implementing Level-3 BLAS Routines in OpenCL on Different Processing Units

Kazuya Matsumoto, Naohito Nakasato, Stanislav Sedukhin

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Tags: ATI, ATI Radeon HD 7970, BLAS, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX Titan, OpenCL

October 29, 2014 by hgpu

A Study of the Potential of Locality-Aware Thread Scheduling for GPUs

Cedric Nugteren, Gert-Jan van den Braak, Henk Corporaal

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 580, OpenCL, Task scheduling

September 28, 2014 by hgpu

Optimization of Data-Parallel Scientific Applications on Highly Heterogeneous Modern HPC Platforms

Ziming Zhong

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Matrix multiplication, Numerical simulation, nVidia, Tesla S2050, Thesis

August 27, 2014 by hgpu

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Koushik Mandal

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2075, Thesis

July 23, 2014 by hgpu

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Csaba Nemes

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 570, Tesla K20, Thesis

July 17, 2014 by hgpu

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Bartosz D. Wozniak

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Source codes

Tags: CUBLAS, CUDA, Fluid dynamics, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Package, Python, Tesla K40, Thesis

July 7, 2014 by hgpu

Evaluation of DGEMM Implementation on Intel Xeon Phi Coprocessor

Pawel Gepner, Victor Gamayunov, David L. Fraser, Eric Houdard, Ludovic Sauge, Damien Declat, Mathieu Dubois

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Tags: Algorithms, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, Performance

June 28, 2014 by hgpu

Performance Improvement of Data Mining in Weka through GPU Acceleration

Tiago Augusto Engel, Andrea Schwertner Charao, Manuele Kirsch-Pinheiro, Luiz-Angelo Steffenel

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Tags: Comuter science, CUDA, Data mining, Java, Matrix multiplication, nVidia, nVidia Quadro K 2000, Package, Tesla K20, Tesla M2050

June 13, 2014 by hgpu

Enabling CP2K Application for Exascale Computing with Accelerators using OpenACC and OpenCL

Mariusz Uchronski, Agnieszka Kwiecien, Marcin Gebarowski

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Tags: ATI, ATI Radeon HD 6950, Chemistry, CUDA, Matrix multiplication, Molecular simulation, MPI, nVidia, OpenACC, OpenCL, Sparse matrix, Tesla M2075

May 16, 2014 by hgpu

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680

May 14, 2014 by hgpu

Toward optimised skeletons for heterogeneous parallel architecture with performance cost model

Khari A. Armih

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MapReduce, Matrix multiplication, nVidia, nVidia GeForce GT 520, Thesis

April 21, 2014 by hgpu

On optimization techniques for the matrix multiplication on hybrid CPU+GPU platforms

Luis-Pedro Garcia, Javier Cuenca, Domingo Gimenez

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Tags: Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 590, Tesla K20

April 16, 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

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

Implementing Level-3 BLAS Routines in OpenCL on Different Processing Units

A Study of the Potential of Locality-Aware Thread Scheduling for GPUs

Optimization of Data-Parallel Scientific Applications on Highly Heterogeneous Modern HPC Platforms

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Efficient implementation of computationally intensive algorithms on parallel computing platforms

GiMMiK – Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics

Evaluation of DGEMM Implementation on Intel Xeon Phi Coprocessor

Performance Improvement of Data Mining in Weka through GPU Acceleration

Enabling CP2K Application for Exascale Computing with Accelerators using OpenACC and OpenCL

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Toward optimised skeletons for heterogeneous parallel architecture with performance cost model

On optimization techniques for the matrix multiplication on hybrid CPU+GPU platforms

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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