high performance computing on graphics processing units: hgpu.org

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Accelerating complex brain-model simulations on GPU platforms

H.A. Du Nguyen, Zaid Al-Ars, Georgios Smaragdos, Christos Strydis

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Tags: Biology, CUDA, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 480, Tesla C2075, Tesla K20

March 30, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

Real-time multi-view deconvolution

Benjamin Schmid, Jan Huisken

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Tags: Biology, CUDA, Microscopy, nVidia, nVidia GeForce GTX Titan, Package

March 30, 2015 by hgpu

Parallel Unsteady Flow Line Integral Convolution for High-Performance Dense Visualization

Zi'ang Ding, Zhanping Liu, Yang Yu, Wei Chen

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Tags: CUDA, Fluid dynamics, Image generation, nVidia, nVidia GeForce GTX 590, Visualization

March 28, 2015 by hgpu

Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space

Richard Wilton, Tamas Budavari, Ben Langmead, Sarah J. Wheelan, Steven L. Salzberg, Alexander S. Szalay

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Sequence alignment, Tesla K20

March 28, 2015 by hgpu

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Xiaowen Chu, Chengjian Liu, Kai Ouyang, Ling Sing Yung, Hai Liu, Yiu-Wing Leung

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Tags: Computer science, CUDA, Error recovery, nVidia, nVidia GeForce GTX 780

March 28, 2015 by hgpu

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Cluster computing, Computer science, CUDA, Distributed computing, Energy-efficient computing, GPU cluster, nVidia, Tesla K20

March 25, 2015 by hgpu

Data driven scheduling approach for the multi-node multi-GPU Cholesky decomposition

Yuki Tsujita, Toshio Endo

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Tags: Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Task scheduling, Tesla K20

March 25, 2015 by hgpu

Curracurrong: a stream processing system for distributed environments

Vasvi Kakkad

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Tags: Algorithms, Computer science, CUDA, OpenCL, Thesis

March 23, 2015 by hgpu

Massively Parallel Construction of the Cell Graph

Krzysztof Kaczmarski, Pawel Rzazewski, Albert Wolant

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Tags: Algorithms, Computer science, CUDA, nVidia, Robotics, Tesla K40

March 23, 2015 by hgpu

A Financial Benchmark for GPGPU Compilation

Christian Andreetta, Vivien Begot, Jost Berthold, Martin Elsman, Troels Henriksen, Maj-Britt Nordfang, Cosmin E. Oancea

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Tags: Benchmarking, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780 Ti

March 23, 2015 by hgpu

PTX2Kernel: Converting PTX Code into Compilable Kernels

Qiankun Dong, Tao Li, Shuai Zhang, Xiaofan Jiao, Jiabing Leng

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 480, PTX, Tesla K40

March 22, 2015 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

Accelerating complex brain-model simulations on GPU platforms

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Real-time multi-view deconvolution

Parallel Unsteady Flow Line Integral Convolution for High-Performance Dense Visualization

Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

Data driven scheduling approach for the multi-node multi-GPU Cholesky decomposition

Curracurrong: a stream processing system for distributed environments

Massively Parallel Construction of the Cell Graph

A Financial Benchmark for GPGPU Compilation

PTX2Kernel: Converting PTX Code into Compilable Kernels

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Tutoring LLM into a Better CUDA Optimizer

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