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Design and Performance Analysis of Parallel Processing of SRTP Packets

Jan Wozniak

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Tags: Computer science, Intel, OpenCL, Security

April 26, 2013 by hgpu

Accelerating Population Balance Model-based particulate process simulations via parallel computing

Anuj Varghese Prakash

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Tags: Biochemistry, Chemistry, Computer science, CUDA, Distributed computing, nVidia, nVidia GeForce GTX 280, Thesis

April 26, 2013 by hgpu

High Performance Computing with GPUs

Nikita Vakulin, Riley Shaw, Timothy Livingston

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Tags: Computer science, CUDA, Differential equations, Finite element method, nVidia, Package

April 25, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Reduce, Reuse, Recycle (R^3): a Design Methodology for Sparse Matrix Vector Multiplication on Reconfigurable Platforms

Kevin Townsend, Joseph Zambreno

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla M2090, Tesla S1070

April 23, 2013 by hgpu

Parallel Computing for Accelerated Texture Classification with Local Binary Pattern Descriptors using OpenCL

CYN Dwith, Rathna.G.N

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Tags: Algorithms, ATI, Computer science, Heterogeneous systems, OpenCL, Pattern recognition

April 23, 2013 by hgpu

Solving Wave Equations on Unstructured Geometries

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: Computer science, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Python, Wave equation

April 23, 2013 by hgpu

GPU Scripting and Code Generation with PyCUDA

Andreas Klockner, Nicolas Pinto, Bryan Catanzaro, Yunsup Lee, Paul Ivanov, Ahmed Fasih

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, PyOpenCL, Python

April 23, 2013 by hgpu

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 570, nVidia GeForce GTX 690, Package, Sequence alignment, Smith-Waterman algorithm

April 23, 2013 by hgpu

GPU-based Implementation of 128-bit Secure Eta Pairing Over a Binary Field

Utsab Bose, Anup Kumar Bhattacharya, Abhijit Das

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Tags: Algorithms, Computer science, CUDA, Elliptic curves, nVidia, nVidia GeForce GTX 480, Security, Tesla C2050

April 22, 2013 by hgpu

Automatic Parallelization of a Gap Model using Java and OpenCL

Jonathan Passerat-Palmbach, Arthur Forest, Julien Pal, Bruno Corbara, D.R.C. Hill

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Tags: Computer science, Java, nVidia, nVidia GeForce GTX 590, OpenCL, Tesla C1060, Tesla C2050

April 22, 2013 by hgpu

On the Efficacy of GPU-Integrated MPI for Scientific Applications

Ashwin M. Aji, Lokendra S. Panwar, Feng Ji, Milind Chabbi, Karthik Murthy, Pavan Balaji, Keith R. Bisset, James Dinan, Wu-chun Feng, John Mellor-Crummey, Xiaosong May, Rajeev Thakur

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, Optimization, Seismology, Tesla M2050

April 22, 2013 by hgpu

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

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

SeedFold: Scaling Biomolecular Structure Prediction

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

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

BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design

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

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

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

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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