high performance computing on graphics processing units: hgpu.org

hgpu.org » Deep learning

Device Placement Optimization with Reinforcement Learning

Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

View

Download (PDF)

Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, Neural networks, nVidia, TensorFlow, Tesla K80

June 17, 2017 by hgpu

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Priya Goyal, Piotr Dollar, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, Kaiming He

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla P100

June 10, 2017 by hgpu

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Java, Neural networks, nVidia, Package, RNN, TensorFlow

June 10, 2017 by hgpu

Neneta: Heterogeneous Computing Complex-Valued Neural Network Framework

Vladimir Lekic, Zdenka Babic

View

Download (PDF)

Tags: ATI, ATI Radeon HD 5770, Computer science, Deep learning, Heterogeneous systems, Neural networks, OpenCL

June 5, 2017 by hgpu

Optimizing Memory Efficiency for Convolution Kernels on Kepler GPUs

Xiaoming Chen, Jianxu Chen, Danny Z. Chen, Xiaobo Sharon Hu

View

Download (PDF)

Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Tesla K40

June 1, 2017 by hgpu

Implementing Efficient, Portable Computations for Machine Learning

Matthew Walter Moskewicz

View

Download (PDF)

Source codes

Tags: Algorithms, AMD R9 Nano, ATI, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

May 24, 2017 by hgpu

Espresso: Efficient Forward Propagation for BCNNs

Fabrizio Pedersoli, George Tzanetakis, Andrea Tagliasacchi

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 960

May 24, 2017 by hgpu

Efficient Parallel Methods for Deep Reinforcement Learning

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

View

Download (PDF)

Source codes

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

May 18, 2017 by hgpu

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

Xinyu Zhang, Srinjoy Das, Ojash Neopane, Ken Kreutz-Delgado

View

Download (PDF)

Tags: Algorithms, Computer science, Computer vision, Deep learning, DSP, FPGA, Neural networks

May 11, 2017 by hgpu

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

Weihua Guo, You Xu, Xueyang Feng

View

Download (PDF)

Source codes

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

May 11, 2017 by hgpu

Acceleration of Deep Learning on FPGA

Huyuan Li

View

Download (PDF)

Tags: CNN, Computer science, Deep learning, FPGA, Neural networks, nVidia, OpenCL, Tesla K40, Thesis

May 9, 2017 by hgpu

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks

Minsoo Rhu, Mike O'Connor, Niladrish Chatterjee, Jeff Pool, Stephen W. Keckler

View

Download (PDF)

Tags: Compression, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, Virtualization

May 6, 2017 by hgpu

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

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

No More Shading Languages: Compiling C++ to Vulkan Shaders

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Device Placement Optimization with Reinforcement Learning

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

Neneta: Heterogeneous Computing Complex-Valued Neural Network Framework

Optimizing Memory Efficiency for Convolution Kernels on Kepler GPUs

Implementing Efficient, Portable Computations for Machine Learning

Espresso: Efficient Forward Propagation for BCNNs

Efficient Parallel Methods for Deep Reinforcement Learning

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

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

Acceleration of Deep Learning on FPGA

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks

Recent source codes

Specx: Speculative task-based runtime system

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

KISim: Kubernetes Intelligent Scheduling Simulator

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

Most viewed papers (last 30 days)