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AutOMP: An Automatic OpenMP Parallelization Generator for Variable-Oriented High-Performance Scientific Codes

Gal Oren, Yehuda Ganan, Guy Malamud

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Tags: Code generation, Computer science, Intel Xeon Phi, OpenMP, Performance

August 1, 2017 by hgpu

Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL?

Ammar Ahmad Awan, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda

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Tags: Computer science, CUDA, Deep learning, GPU cluster, MPI, nVidia, nVidia DGX-1, OpenMPI, Tesla V100

August 1, 2017 by hgpu

Deep Architectures for Neural Machine Translation

Antonio Valerio Miceli Barone, Jindrich Helcl, Rico Sennrich, Barry Haddow, Alexandra Birch

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, nVidia GeForce GTX Titan X, Package, Theano

August 1, 2017 by hgpu

Directive-Based Partitioning and Pipelining for Graphical Processing Units

X. Cui, T. R. W. Scogland, B. R. de Supinski, W. Feng

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, OpenACC, OpenCL, OpenMP, Performance, Task scheduling, Tesla K40

August 1, 2017 by hgpu

On Simplifying and Optimizing Programs for Heterogeneous Computing Systems

Ivan Grasso

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Tags: AMD FirePro S9000, ATI, ATI Radeon HD 5870, Compilers, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla K20, Thesis

July 25, 2017 by hgpu

FUX-Sim: Implementation of a fast universal simulation/reconstruction framework for X-ray systems

Monica Abella, Estefania Serrano, Javier Garcia-Blas, Ines Garcia, Claudia de Molina, Jesus Carretero, Manuel Desco

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, OpenCL, Tesla K40

July 25, 2017 by hgpu

ParTeCL: parallel testing using OpenCL

Vanya Yaneva, Ajitha Rajan, Christophe Dubach

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Tags: Benchmarking, Compilers, Computer science, OpenCL, Package

July 25, 2017 by hgpu

OpenCL Library for Parallel Graph Search Algorithms

Christian Fischer

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, OpenCL, Path problems, Thesis

July 25, 2017 by hgpu

Memory-Efficient Implementation of DenseNets

Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger

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Tags: Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package, Tesla M40, Torch

July 25, 2017 by hgpu

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

Francesc Sastre Cabot

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, Tesla K80, Tesla M2090, Thesis

July 22, 2017 by hgpu

A Comparison of Support Vector Machines Training GPU-Accelerated Open Source Implementations

Jan Vanek, Josef Michalek, Josef Psutka

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Tags: Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

July 22, 2017 by hgpu

GPU accelerated computation of Polarized Subsurface BRDF for Flat Particulate Layers

Charly Collin, Sumanta Pattanaik

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Tags: Computer science, Differential equations, Graphics, nVidia, nVidia GeForce GTX 580, OpenCL, Rendering

July 22, 2017 by hgpu

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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high performance computing on graphics processing units: hgpu.org

AutOMP: An Automatic OpenMP Parallelization Generator for Variable-Oriented High-Performance Scientific Codes

Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL?

Deep Architectures for Neural Machine Translation

Directive-Based Partitioning and Pipelining for Graphical Processing Units

On Simplifying and Optimizing Programs for Heterogeneous Computing Systems

FUX-Sim: Implementation of a fast universal simulation/reconstruction framework for X-ray systems

ParTeCL: parallel testing using OpenCL

OpenCL Library for Parallel Graph Search Algorithms

Memory-Efficient Implementation of DenseNets

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

A Comparison of Support Vector Machines Training GPU-Accelerated Open Source Implementations

GPU accelerated computation of Polarized Subsurface BRDF for Flat Particulate Layers

Recent source codes

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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