high performance computing on graphics processing units: hgpu.org

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Acceleration of iterative Navier-Stokes solvers on graphics processing units

Tomczak, T., Zadarnowska, K., Koza, Z., Matyka, M., Miroslaw, L.

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Tags: CUDA, Finite volume method, Fluid dynamics, GPU, hardware acceleration, incompressible flow, Navier-Stokes solvers, OpenFOAM, operator splitting, Parallelization, PISO, SIMPLE

September 9, 2013 by Vratis

Adaptive Partial STEM

Advances in Electron Microscopy with Deep Learning

Linus: easy-to-share, interactive 3D figures

linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser

Compound Word Transformer

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

SAPFOR

Interactive Parallelization of C Programs in SAPFOR

CUDA Memtrace

Exploiting BSP Abstractions for Compiler Based Optimizations of GPU Applications on multi-GPU Systems

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

waLBerla: (widely applicable Lattice Boltzmann from Erlangen), massively parallel framework for multi physics applications

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Systolic CNN

Systolic-CNN: An OpenCL-defined Scalable Run-time-flexible FPGA Accelerator Architecture for Accelerating Convolutional Neural Network Inference in Cloud/Edge Computing

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

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