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A GEMM interface and implementation on NVIDIA GPUs for multiple small matrices

Chetan Jhurani, Paul Mullowney

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Tags: BLAS, CUBLAS, CUDA, Dense linear algebra, GEMM, Linear Algebra, nVidia, Parallel programming, Tesla K20

April 9, 2013 by chetan.jhurani

Futhark

Bounds Checking on GPU

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

Stanza: A Python NLP Library for Many Human Languages

Biomedical and Clinical English Model Packages in the Stanza Python NLP Library

Benchmark for sparse-dense matrix multiplications

Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM

Darknet on OpenCL: a multi-platform tool for object detection and classification

Darknet on OpenCL: a multi-platform tool for object detection and classification

3DES on Nvidia GPUs

Bit-level Parallelization of 3DES Encryption on GPU

SONIC: (Services for Optimized Network Inference on Coprocessors) for CMS

GPU coprocessors as a service for deep learning inference in high energy physics

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads

Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads

ComPyle: execute a subset of Python on HPC platforms

Compyle: a Python package for parallel computing

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