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Synchronization and Coordination in Heterogeneous Processors

Joel Hestness

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 860 M, OpenCL, Thesis

January 8, 2017 by hgpu

A Framework for Dense Triangular Matrix Kernels on Various Manycore Architectures

Ali Charara, David Keyes, Hatem Ltaief

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Tags: BLAS, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, Matrix multiplication, nVidia, Package, Tesla K40

January 8, 2017 by hgpu

Akid: A Library for Neural Network Research and Production from a Dataism Approach

Shuai Li

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Tags: Computer science, CUDA, Deep learning, Distributed computing, Machine learning, Neural networks, nVidia, Package, Python, TensorFlow

January 8, 2017 by hgpu

Gunrock: GPU Graph Analytics

Yangzihao Wang, Yuechao Pan, Andrew Davidson, Yuduo Wu, Carl Yang, Leyuan Wang, Muhammad Osama, Chenshan Yuan, Weitang Liu, Andy T. Riffel, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 8, 2017 by hgpu

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

Daniel George, E. A. Huerta

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Tags: Algorithms, Artificial intelligence, Astrophysics, CUDA, Deep learning, Filtering, Gravitation, Gravitational waves, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, Physics, Signal processing, Tesla K40, Tesla P100

January 4, 2017 by hgpu

Massively Parallel Computation of Accurate Densities for N-body Dark Matter Simulations using the Phase-Space-Element Method

Ralf Kaehler

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Tags: Astrophysics, Computational Physics, CUDA, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Package, Physics, Tesla K80, Tessellation

January 4, 2017 by hgpu

Design and optimization of a portable LQCD Monte Carlo code using OpenACC

Claudio Bonati, Enrico Calore, Simone Coscetti, Massimo D'Elia, Michele Mesiti, Francesco Negro, Sebastiano Fabio Schifano, Giorgio Silvi, Raffaele Tripiccione

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Tags: AMD FirePro W9100, ATI, Computational Physics, Heterogeneous systems, High Energy Physics - Lattice, nVidia, OpenACC, performance portability, Physics, QCD, Tesla K80, Tesla P100

January 4, 2017 by hgpu

Synthesizing Benchmarks for Predictive Modeling

Chris Cummins, Pavlos Petoumenos, Zheng Wang, Hugh Leather

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Compilers, Computer science, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan, OpenCL, Package

December 31, 2016 by hgpu

Automatic OpenCL Task Adaptation for Heterogeneous Architectures

Pierre Huchant, Marie-Christine Counilh, Denis Barthou

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Tags: Compilers, Computer science, Heterogeneous systems, nVidia, nVidia Quadro K5000, OpenCL, Tesla K20, Tesla M2075

December 31, 2016 by hgpu

Android Malware Classification Using Parallelized Machine Learning Methods

Lifan Xu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, OpenMP, Security, Tesla C2050, Thesis

December 31, 2016 by hgpu

Parallel Digital Predistortion Design on Mobile GPU and Embedded Multicore CPU for Mobile Transmitters

Kaipeng Li, Amanullah Ghazi, Chance Tarver, Jani Boutellier, Mahmoud Abdelaziz, Lauri Anttila, Markku Juntti, Mikko Valkama, Joseph R. Cavallaro

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Tags: ARM, CUDA, nVidia, nVidia Jetson TK1, nVidia Tegra TX1, Signal processing, SoC

December 31, 2016 by hgpu

Language Modeling with Gated Convolutional Networks

Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, Performance, Tesla M40, Torch

December 26, 2016 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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