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Reuse and Refactoring of GPU Kernels to Design Complex Applications

Santonu Sarkar, Sayantan Mitra, Ashok Srinivasan

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Tags: Computer science, CUDA, FFT, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Optimization, Software Engineering, Tesla S1050

February 24, 2012 by hgpu

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Heterogeneous parallel computing for image registration and linear algebra applications

Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters

Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters

PERCH 2.0: Fast and High-Quality GPU-based Perception via Search for Object Pose Estimation

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

AnyHLS: High-Level Synthesis with Partial Evaluation

AnyHLS: High-Level Synthesis with Partial Evaluation

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

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2020

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Naha, Okinawa, Japan

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

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