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Feynman Machine: The Universal Dynamical Systems Computer

Eric Laukien, Richard Crowder, Fergal Byrne

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Tags: AMD Radeon R9 290, Artificial intelligence, ATI, Computer science, Deep learning, Mathematics, Neuroscience, OpenCL

September 20, 2016 by hgpu

Accelerating Exact and Approximate Inference for (Distributed) Discrete Optimization with GPUs

Ferdinando Fioretto, Enrico Pontelli, William Yeoh, Rina Dechter

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Tags: Algorithms, Artificial intelligence, Bayesian, Computer science, nVidia, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan X, Optimization, Package, Tesla M2075

August 23, 2016 by hgpu

TensorFlow: A system for large-scale machine learning

Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeFofce GTX Titan X, Package, Tesla K40

May 30, 2016 by hgpu

Deep Learning on FPGAs: Past, Present, and Future

Griffin Lacey, Graham W. Taylor, Shawki Areibi

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Machine learning, OpenCL, Overview

February 17, 2016 by hgpu

Origami: A Convolutional Network Accelerator

Lukas Cavigelli, David Gschwend, Christoph Mayer, Samuel Willi, Beat Muheim, Luca Benini

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Tags: Algorithms, Artificial intelligence, ASIC, Computer science, Computer vision, Machine learning, Neural networks

December 15, 2015 by hgpu

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Vincenzo Lomonaco

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Pattern recognition, Tesla C2075, Thesis

November 8, 2015 by hgpu

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Fabian Tschopp

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Tags: AMD FirePro W9100, Artificial intelligence, ATI, Caffe, CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Thesis

September 15, 2015 by hgpu

Parallel Execution of the ASP Computation – an Investigation on GPUs

Agostino Dovier, Andrea Formisano, Enrico Pontelli, Flavio Vella

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce GT 520, nVidia GeForce GT 640, nVidia GeForce GTX Titan X, Search strategies, Tesla C2075, Tesla K20, Tesla K80

September 5, 2015 by hgpu

Scaling Monte Carlo Tree Search on Intel Xeon Phi

S. Ali Mirsoleimani, Aske Plaat, Jaap van den Herik, Jos Vermaseren

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Tags: Algorithms, Artificial intelligence, Computer science, Intel Xeon Phi, Package

July 17, 2015 by hgpu

Improving CUDA DNA Analysis Software with Genetic Programming

William B. Langdon, Brian Yee Hong Lam, Justyna Petke, Mark Harman

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Tags: Algorithms, Artificial intelligence, Bioinformatics, Computer science, CUDA, Genetic programming, nVidia, Package, Tesla K20, Tesla K40

May 12, 2015 by hgpu

A Review on Parallelization of Node based Game Tree Search Algorithms on GPU

Rutuja U. Gosavi, Payal S. Kulkarni

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia

December 20, 2014 by hgpu

Massively Parallel A* Search on a GPU

Yichao Zhou, Jianyang Zeng

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, Tesla K20

December 7, 2014 by hgpu

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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