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MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Michail Alvanos, Theodoros Christoudias

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Tags: Chemistry, Compilers, Computer science, CUDA, Fortran, nVidia, Package, Python

May 22, 2017 by hgpu

Inferring the Scheduling Policies of an Embedded CUDA GPU

Nathan Otterness, Ming Yang, Tanya Amert, James H. Anderson, F. Donelson Smith

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Tegra TX1, Package, Task scheduling

May 22, 2017 by hgpu

CLBlast: A Tuned OpenCL BLAS Library

Cedric Nugteren

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Tags: AMD Radeon R9 M370X, ARM, ATI, BLAS, Computer science, Intel HD 5100, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan X, OpenCL, Package

May 18, 2017 by hgpu

Efficient Parallel Methods for Deep Reinforcement Learning

Alfredo V. Clemente, Humberto N. Castejon, Arjun Chandra

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GXT 980 Ti, Package, Python, TensorFlow

May 18, 2017 by hgpu

Block-Parallel IDA* for GPUs

Satoru Horie, Alex Fukunaga

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GRID K520, Package

May 11, 2017 by hgpu

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Weihua Guo, You Xu, Xueyang Feng

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Tags: Biology, Computer science, Deep learning, Medicine, nVidia, nVidia GeForce GTX 1080, Package, Python, TensorFlow

May 11, 2017 by hgpu

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Konstantinos Krommydas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Performance, Tesla K20, Thesis

May 9, 2017 by hgpu

Efficient Parallel Strategy Improvement for Parity Games

John Fearnley

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Logic in Computer Science, nVidia, nVidia GeForce GTX 780, Package

May 9, 2017 by hgpu

Fast Sorting Algorithms using AVX-512 on Intel Knights Landing

Berenger Bramas

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Sorting

May 9, 2017 by hgpu

cuTT: A High-Performance Tensor Transpose Library for CUDA Compatible GPUs

Antti-Pekka Hynninen, Dmitry I. Lyakh

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, nVidia, Package, Tesla K20, Tesla K40, Tesla M40, Tesla P100

May 6, 2017 by hgpu

Low-complexity Distributed Tomographic Backprojection for large datasets

Gilberto Martinez Jr., Janito V. Ferreira Filho, Eduardo X. Miqueles

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, nVidia GeForce GTX X, nVidia Tegra TX1, Package, Tomography

April 30, 2017 by hgpu

A Training Framework and Architectural Design for Distributed Deep Learning

Wei Wang

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan X, Package, Python, Thesis

April 26, 2017 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

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high performance computing on graphics processing units: hgpu.org

Applications

MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Inferring the Scheduling Policies of an Embedded CUDA GPU

CLBlast: A Tuned OpenCL BLAS Library

Efficient Parallel Methods for Deep Reinforcement Learning

Block-Parallel IDA* for GPUs

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Efficient Parallel Strategy Improvement for Parity Games

Fast Sorting Algorithms using AVX-512 on Intel Knights Landing

cuTT: A High-Performance Tensor Transpose Library for CUDA Compatible GPUs

Low-complexity Distributed Tomographic Backprojection for large datasets

A Training Framework and Architectural Design for Distributed Deep Learning

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