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High Performance Approximate Sort Algorithm Using GPUs

Jun Xiao, Hao Chen, Jianhua Sun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Sorting

July 3, 2015 by hgpu

Modelling the Formation of Ordered Acentrosomal Microtubule Arrays

Alexander Ross Mace

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Tags: Biology, Computer science, Monte Carlo simulation, OpenCL, Probability, Thesis

July 3, 2015 by hgpu

Texture Cache Approximation on GPUs

Mark Sutherland, Joshua San Miguel, Natalie Enright Jerger

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Performance

July 3, 2015 by hgpu

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Andrea Miele

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan Black, Security

July 1, 2015 by hgpu

Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

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Tags: Computer science, CUDA, Data mining, Deep learning, Machine learning, nVidia, Tesla K40

July 1, 2015 by hgpu

Accelerating DNA Sequence Analysis using Intel Xeon Phi

Suejb Memeti, Sabri Pllana

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Tags: Bioinformatics, Computer science, Intel Xeon Phi, OpenMP, Performance

July 1, 2015 by hgpu

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Andre Viebke, Sabri Pllana

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Tags: CNN, Computer science, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Performance

July 1, 2015 by hgpu

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Amir Gholami, Judith Hill, Dhairya Malhotra, George Biros

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Tags: Algorithms, Computer science, CUDA, FFT, MPI, nVidia, OpemMP, Package, Tesla K20

June 30, 2015 by hgpu

Intra-Application Data-Communication Characterization

Imran Ashraf, Vlad-Mihai Sima, Koen Bertels

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 640

June 30, 2015 by hgpu

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Marijn F. Stollenga, Wonmin Byeon, Marcus Liwicki, Juergen Schmidhuber

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Tags: Computer science, CUDA, Deep learning, Image processing, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan X

June 26, 2015 by hgpu

Concurrent Solutions to Linear Systems using Hybrid CPU/GPU Nodes

Oluwapelumi Adenikinju, Julian Gilyard, Joshua Massey, Thomas Stitt

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Tags: Computer science, CUDA, Linear Algebra, nVidia, OpenGL, OpenMP

June 26, 2015 by hgpu

Composability of parallel codes on heterogeneous architectures

Andra-Ecaterina Hugo

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Sparse direct solvers, Tesla M2070, Thesis

June 26, 2015 by hgpu

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

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

High Performance Approximate Sort Algorithm Using GPUs

Modelling the Formation of Ordered Acentrosomal Microtubule Arrays

Texture Cache Approximation on GPUs

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Heterogeneous Network Embedding via Deep Architectures

Accelerating DNA Sequence Analysis using Intel Xeon Phi

The Potential of the Intel Xeon Phi for Supervised Deep Learning

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Intra-Application Data-Communication Characterization

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Concurrent Solutions to Linear Systems using Hybrid CPU/GPU Nodes

Composability of parallel codes on heterogeneous architectures

Recent source codes

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

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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