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An Efficient Implementation of the Longest Common Subsequence Algorithm with Bit-Parallelism on GPUs

Katsuya Kawanami

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 580, Thesis

March 25, 2016 by hgpu

Wanted: Floating-Point Add Round-off Error instruction

Marat Dukhan, Richard Vuduc, Jason Riedy

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Tags: Computer science, CUDA, Matrix multiplication, OpenCL, Package

March 25, 2016 by hgpu

Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent

Linnan Wang, Yi Yang, Martin Renqiang Min, Srimat Chakradhar

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Tags: Caffe, Computer science, CUDA, Data parallelism, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

March 25, 2016 by hgpu

A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Lukas Einkemmer

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Tags: Computational Physics, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, Mixed precision, nVidia, OpenMP, Tesla K80

March 25, 2016 by hgpu

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Torbjorn Sorman

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Tags: AMD Radeon R7 260X, ATI, Benchmarking, Computer science, DirectCompute, DirectX, nVidia, nVidia GeForce GTX 670, OpenCL, OpenGL, Performance, Thesis

March 22, 2016 by hgpu

Proteus: Efficient Resource Use in Heterogeneous Architectures

Sankaralingam Panneerselvam, Michael M. Swift

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 650, nVidia GeForce GTX 670, OpenCL, Task scheduling

March 22, 2016 by hgpu

Recurrent neural networks for language modeling

Emil Sauer Lynge

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Tags: Computer science, CUDA, Deep learning, LSTM, Neural networks, NLP, nVidia, nVidia GeForce GTX Titan X, Package, Python, RNN, Thesis

March 22, 2016 by hgpu

OpenCL Cryptographic Library

Martin Preisler

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Tags: AES, Algorithms, Computer science, Intel HD Graphics 4000, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 580, OpenCL, Security, Thesis

March 20, 2016 by hgpu

A Massively Parallel Algorithm for Cell Classification Using CUDA

Samuel Schmidt

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Tags: Bioinformatics, Biology, CUDA, Machine learning, nVidia, nVidia GeForce GTX 770, RNA, Thesis

March 20, 2016 by hgpu

Automatic Detection and Denoising of Signals in Large Geophysical Datasets

Gabriel O. Trisca

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Tags: Aparapi, Computer science, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan, OpenCL, RNN, Seismology, Sensing, Signal denoising, Tesla K20, Thesis

March 20, 2016 by hgpu

Acceleration of ensemble machine learning methods using many-core devices

A. Tamerus, A. Washbrook, D. Wyeth

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Tags: Computer science, CUDA, Machine learning, nVidia, Physics, Tesla K40

March 20, 2016 by hgpu

Analyzing and Improving the Performance of Spatial Database Processing

Bogdan Simion

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Thesis

March 20, 2016 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

An Efficient Implementation of the Longest Common Subsequence Algorithm with Bit-Parallelism on GPUs

Wanted: Floating-Point Add Round-off Error instruction

Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent

A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Proteus: Efficient Resource Use in Heterogeneous Architectures

Recurrent neural networks for language modeling

OpenCL Cryptographic Library

A Massively Parallel Algorithm for Cell Classification Using CUDA

Automatic Detection and Denoising of Signals in Large Geophysical Datasets

Acceleration of ensemble machine learning methods using many-core devices

Analyzing and Improving the Performance of Spatial Database Processing

Recent source codes

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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