high performance computing on graphics processing units: hgpu.org

hgpu.org » CUDA

Splotch: porting and optimizing for the Xeon Phi

Timothy Dykes, Claudio Gheller, Marzia Rivi, Mel Krokos

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Intel Xeon Phi, Numerical simulation, nVidia, OpenCL, Package, Tesla K20, Visualization

June 16, 2016 by hgpu

NCAM: Near-Data Processing for Nearest Neighbor Search

Vincent T. Lee, Carlo C. del Mundo, Armin Alaghi, Luis Ceze, Mark Oskin, Ali Farhadi

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, nVidia Jetson TK1

June 16, 2016 by hgpu

Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs

Stefan Hadjis, Ce Zhang, Ioannis Mitliagkas, Christopher Re

View

Download (PDF)

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

June 16, 2016 by hgpu

Multi-Tenant Virtual GPUs for Optimising Performance of a Financial Risk Application

Javier Prades, Blesson Varghese, Carlos Reano, Federico Silla

View

Download (PDF)

Tags: Computer science, CUDA, Finance, nVidia, Tesla K20

June 16, 2016 by hgpu

Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Erik Zenker, Rene Widera, Axel Hubl, Guido Juckeland, Andreas Knupfer, Wolfgang E. Nagel, Michael Bussmann

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Package, Particle-in-cell methods, Physics, Plasma physics, Programming techniques, Tesla K80

June 14, 2016 by hgpu

Processing Big Data in Main Memory and on GPU

Meisam Fathi Salmi

View

Download (PDF)

Tags: big data, Computer science, CUDA, Hadoop, Java, OpenCL, Scala, Spark, Thesis

June 14, 2016 by hgpu

Multi-GPU Implementation of Machine Learning Algorithm using CUDA and OpenCL

Jan Masek, Radim Burget, Lukas Povoda, Malay Kishore Dutta

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 690, OpenCL

June 14, 2016 by hgpu

Decoupled Vector-Fetch Architecture with a Scalarizing Compiler

Yunsup Lee

View

Download (PDF)

Tags: Computer science, CUDA, Electronic design automation, Heterogeneous systems, LLVM, OpenCL, Performance, PTX, SoC, Thesis

June 9, 2016 by hgpu

Adaptive Multi-level Blocking Optimization for Sparse Matrix Vector Multiplication on GPU

Yusuke Nagasaka, Akira Nukada, Satoshi Matsuoka

View

Download (PDF)

Tags: Computer science, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla K20

June 9, 2016 by hgpu

Runtime Specialization for Heterogeneous CPU-GPU Platforms

Naila Farooqui

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7770, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, PTX, Tesla C2050, Tesla M2075, Thesis

June 9, 2016 by hgpu

Massively-Parallel Lossless Data Decompression

Evangelia Sitaridi, Rene Mueller, Tim Kaldewey, Guy Lohman, Kenneth Ross

View

Download (PDF)

Tags: Algorithms, Compression, Computer science, CUDA, nVidia, Tesla K40

June 7, 2016 by hgpu

Bit-Vectorized GPU Implementation of a Stochastic Cellular Automaton Model for Surface Growth

Jeffrey Kelling, Geza Odor, Sibylle Gemming

View

Download (PDF)

Tags: Computational Physics, Computer science, CUDA, Materials Science, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce Titan Black, Statistical Mechanics, Tesla K80

June 7, 2016 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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Splotch: porting and optimizing for the Xeon Phi

NCAM: Near-Data Processing for Nearest Neighbor Search

Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs

Multi-Tenant Virtual GPUs for Optimising Performance of a Financial Risk Application

Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Processing Big Data in Main Memory and on GPU

Multi-GPU Implementation of Machine Learning Algorithm using CUDA and OpenCL

Decoupled Vector-Fetch Architecture with a Scalarizing Compiler

Adaptive Multi-level Blocking Optimization for Sparse Matrix Vector Multiplication on GPU

Runtime Specialization for Heterogeneous CPU-GPU Platforms

Massively-Parallel Lossless Data Decompression

Bit-Vectorized GPU Implementation of a Stochastic Cellular Automaton Model for Surface Growth

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

Most viewed papers (last 30 days)