high performance computing on graphics processing units: hgpu.org

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Explicit Shallow Water Simulations on GPUs: Guidelines and Best Practices

Andre R. Brodtkorb, Martin L. Saetra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580

June 27, 2012 by hgpu

A Parallel Monte Carlo Code for Simulating Collisional N-body Systems

Bharath Pattabiraman, Stefan Umbreit, Wei-Keng Liao, Alok Choudhary, Vassiliki Kalogera, Gokhan Memik, Frederic A. Rasio

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, MPI, N-body simulation, Nearest neighbour, nVidia, nVidia GeForce GTX 280, Sorting

June 27, 2012 by hgpu

GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures

Kai Ma, Xue Li, Wei Chen, Chi Zhang, Xiaorui Wang

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX

June 26, 2012 by hgpu

Multi-GPU Island-Based Genetic Algorithm for Solving the Knapsack Problem

Jiri Jaros

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Tags: Algorithms, Computer science, CUDA, Genetic programming, GPU cluster, MPI, nVidia, nVidia GeForce GTX 580, Package

June 26, 2012 by hgpu

Compiling a high-level language for GPUs: (via language support for architectures and compilers)

Christophe Dubach, Perry Cheng, Rodric Rabbah, David F. Bacon, Stephen J. Fink

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Tags: ATI, ATI Radeon HD 5970, Compilers, Computer science, CUDA, Heterogeneous systems, Java, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 580, OpenCL, Programming Languages

June 26, 2012 by hgpu

A Parallel Algorithm Development Model for the GPU Architecture

J. Steven Kirtzic, Ovidiu Daescu

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Tags: Algorithms, Computer science, CUDA, nVidia

June 25, 2012 by hgpu

Improving GPU Simulations of Spiking Neural P Systems

Francis George C. Cabarle, Henry N. Adorna, Miguel A. Martinez-Del-Amor, Mario J. Perez-Jimenez

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Tags: Computer science, CUDA, Linear Algebra, Membrane computing, Neural networks, nVidia, P systems, Tesla C1060

June 25, 2012 by hgpu

GPU Implementation of the Branch and Bound method for knapsack problems

Mohamed Esseghir Lalami, Didier El-Baz

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Tags: Computer science, CUDA, Hybrid computing, nVidia, Optimization, Tesla C2050

June 25, 2012 by hgpu

An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem

Imen Chakroun, Nouredine Melab

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Tags: Computer science, CUDA, GPU cluster, nVidia, Optimization, Tesla S1070

June 25, 2012 by hgpu

Fast motion detection from airborne videos using graphics processing unit

Kui Liu, Ben Ma, Qian Du, Genshe Chen

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, Optical flow

June 23, 2012 by hgpu

GPU-accelerated Model Checking of Periodic Self-Suspending Real-Time Tasks

Per-Erik Mahl, Tim Liberg

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 320 M, nVidia GeForce GTX 275, Task scheduling, Thesis

June 23, 2012 by hgpu

High performance implementation of hydrodynamic interactions and applications with the sub-cellular element method

Andrei Frunza

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Tags: Computer science, CUDA, Diffusion tensor, nVidia, nVidia GeForce GTX 580, Physics, Thesis

June 21, 2012 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Explicit Shallow Water Simulations on GPUs: Guidelines and Best Practices

A Parallel Monte Carlo Code for Simulating Collisional N-body Systems

GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures

Multi-GPU Island-Based Genetic Algorithm for Solving the Knapsack Problem

Compiling a high-level language for GPUs: (via language support for architectures and compilers)

A Parallel Algorithm Development Model for the GPU Architecture

Improving GPU Simulations of Spiking Neural P Systems

GPU Implementation of the Branch and Bound method for knapsack problems

An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem

Fast motion detection from airborne videos using graphics processing unit

GPU-accelerated Model Checking of Periodic Self-Suspending Real-Time Tasks

High performance implementation of hydrodynamic interactions and applications with the sub-cellular element method

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

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