high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Accelerating a Cloud-Based Software GNSS Receiver

Kamran Karimi, Aleks G. Pamir, M. Haris Afzal

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Tags: Cloud, Computer science, CUDA, nVidia, nVidia GeForce GTX 550 Ti, Performance

September 4, 2013 by hgpu

Bitcoin and The Age of Bespoke Silicon

Michael Bedford Taylor

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Tags: ASIC, ATI, Finance, FPGA, nVidia, OpenCL, Performance, Review

August 31, 2013 by hgpu

Efficient Sparse Matrix-Vector Multiplication on x86-Based Many-Core Processors

Xing Liu, Mikhail Smelyanskiy, Edmond Chow, Pradeep Dubey

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Tags: Algorithms, Computer science, CUDA, Intel Phi, nVidia, Performance, Sparse matrix, Tesla K20

August 29, 2013 by hgpu

In-Situ Statistical Analysis of Autotune Simulation Data using Graphical Processing Units

Niloo Ranjan, Jibonananda Sanyal, Joshua New

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Tesla K20

August 28, 2013 by hgpu

Dynamic Load Balancing on Massively Parallel Computer Architectures

Florian Wende

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Tags: Computer science, CUDA, Intel Phi, nVidia, Performance, Raytracing, Tesla M2090, Thesis

August 28, 2013 by hgpu

SystemC simulation on GP-GPUs: CUDA vs. OpenCL

Nicola Bombier, Sara Vinco, Valeria Bertacco, Debapriya Chatterjee

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 570, OpenCL, Performance

August 26, 2013 by hgpu

Performance Evaluation of Intel Xeon Phi Coprocessor using XKaapi

Joao V. F. Lima, Nicolas Maillard, Franciois Broquedis, Thierry Gautier, Bruno Raffin

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Tags: Benchmarking, Computer science, Intel, Intel Phi, Performance

August 26, 2013 by hgpu

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems: Evaluating the Potential Gains and Systems Effects

Kalyan S. Perumalla, Alfred J. Park

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Particle simulation, Performance, Tesla X2090

August 24, 2013 by hgpu

Comparative Analysis of OpenACC, OpenMP and CUDA using Sequential and Parallel Algorithms

Cleverson Lopes Ledur, Carlos M. D. Zeve, Julio C. S. dos Anjos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 650, OpenACC, OpenMP, Performance

August 21, 2013 by hgpu

Comparison of Cilk, Kaapi and CUDA for the Jacobi Method

Luis Felipe Millani, Nicolas Maillard

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

August 21, 2013 by hgpu

Accurate Analytic Models to Estimate Execution Time on GPU Applications

Pedro Velho, Daniel A. G. de Oliveira, Edson L. Padoin, Philippe O. A. Navaux

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Programming techniques

August 21, 2013 by hgpu

Performance Drawbacks for Matrix Multiplication using Set Associative Cache in GPU devices

Leonid Djinevski, Sime Arsenovski, Sasko Ristov, Marjan Gusev

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

August 19, 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

Bitcoin and The Age of Bespoke Silicon

Efficient Sparse Matrix-Vector Multiplication on x86-Based Many-Core Processors

In-Situ Statistical Analysis of Autotune Simulation Data using Graphical Processing Units

Dynamic Load Balancing on Massively Parallel Computer Architectures

SystemC simulation on GP-GPUs: CUDA vs. OpenCL

Performance Evaluation of Intel Xeon Phi Coprocessor using XKaapi

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems: Evaluating the Potential Gains and Systems Effects

Comparative Analysis of OpenACC, OpenMP and CUDA using Sequential and Parallel Algorithms

Comparison of Cilk, Kaapi and CUDA for the Jacobi Method

Accurate Analytic Models to Estimate Execution Time on GPU Applications

Performance Drawbacks for Matrix Multiplication using Set Associative Cache in GPU devices

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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