Applications

hgpu.org » Applications

Deep neural networks for direct, featureless learning through observation: the case of 2d spin models

K. Mills, I. Tamblyn

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Tags: Condensed matter, CUDA, Deep learning, Ising model, Materials Science, Neural networks, nVidia, Phase transition, Physics, Tesla K40

July 2, 2017 by hgpu

Synthesis of Embedded Software using Dataflow Schedule Graphs

Abhay Raina

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Tags: Computer science, DSP, nVidia, nVidia GeForce GTX 680, OpenCL, Signal processing, Thesis

July 2, 2017 by hgpu

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

Loc N. Huynh, Youngki Lee, Rajesh Krishna Balan

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Tags: Algorithms, Computer science, Deep learning, OpenCL, Package, Vulkan

June 25, 2017 by hgpu

ART vs. NDK vs. GPU acceleration: A study of performance of image processing algorithms on Android

Andreas Palsson

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Tags: Algorithms, Android, Image processing, Java, OpenCL, RenderScript, Thesis

June 25, 2017 by hgpu

Scalar collapse in AdS with an OpenCL open source code

Steven L. Liebling, Gaurav Khanna

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Tags: AMD Radeon R9 295X2, ATI, General Relativity and Quantum Cosmology, Heterogeneous systems, High Energy Physics - Theory, nVidia, OpenCL, Package, Physics, Tesla K40

June 25, 2017 by hgpu

An Analysis of Variation Between Cores For Intel Xeon Phi Knights Corner And Xeon Phi Knights Landing

Jamar Robinson

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Tags: Computer science, Intel Xeon Phi, Performance, Thesis

June 25, 2017 by hgpu

High-Performance Out-of-core Block Randomized Singular Value Decomposition on GPU

Yuechao Lu, Fumihiko Ino, Yasuyuki Matsushita

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Tags: Algorithms, Computer science, Computer vision, CUDA, Linear Algebra, Machine learning, nVidia, Tesla P100

June 25, 2017 by hgpu

Multi-level Parallelism with MPI and OpenACC for CFD Applications

Andrew J. McCall

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Tags: cfd, Fluid dynamics, Fortran, MPI, nVidia, OpenACC, Tesla C2075, Tesla K80, Tesla M2050, Thesis

June 21, 2017 by hgpu

Panda: A Compiler Framework for Concurrent CPU-GPU Execution of 3D Stencil Computations on GPU-accelerated Supercomputers

Mohammed Sourouri, Scott B. Baden, Xing Cai

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Tags: Code generation, Compilers, Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenMP, Tesla K20

June 21, 2017 by hgpu

On the Use of a GPU-Accelerated Mobile Device Processor for Sound Source Localization

Jose A. Belloch, Jose M. Badia, Francisco D. Igual, Maximo Cobos, Enrique S. Quintana-Orti

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Tags: Algorithms, ARM, nVidia, nVidia GeForce GTX 1080, OpenCL, Signal processing, Tesla K20

June 21, 2017 by hgpu

Rgtsvm: Support Vector Machines on a GPU in R

Zhong Wang, Tinyi Chu, Lauren A Choate, Charles G Danko

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Tags: Computer science, CUDA, Machine learning, nVidia, Package, R, Tesla K20

June 21, 2017 by hgpu

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

Keunwoo Choi, Deokjin Joo, Juho Kim

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Tags: Computer science, CUDA, Deep learning, Keras, Neural networks, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan X, Package, Python, Signal processing, Tesla K80, Tesla M60

June 21, 2017 by hgpu

Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

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

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high performance computing on graphics processing units: hgpu.org

Applications

Deep neural networks for direct, featureless learning through observation: the case of 2d spin models

Synthesis of Embedded Software using Dataflow Schedule Graphs

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

ART vs. NDK vs. GPU acceleration: A study of performance of image processing algorithms on Android

Scalar collapse in AdS with an OpenCL open source code

An Analysis of Variation Between Cores For Intel Xeon Phi Knights Corner And Xeon Phi Knights Landing

High-Performance Out-of-core Block Randomized Singular Value Decomposition on GPU

Multi-level Parallelism with MPI and OpenACC for CFD Applications

Panda: A Compiler Framework for Concurrent CPU-GPU Execution of 3D Stencil Computations on GPU-accelerated Supercomputers

On the Use of a GPU-Accelerated Mobile Device Processor for Sound Source Localization

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

Recent source codes

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

INT v.s. FP: A framework to compare low-bit integer and float-point formats

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

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

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