Search Results for 'Gpu-Programming'

Gpu-Programming published presentations and documents on DocSlides.

CULZSS LZSS Lossless Data Compression on CUDA
CULZSS LZSS Lossless Data Compression on CUDA
by bety
Adnan. . Ozsoy. & Martin . Swany. DAMSL - D...
Chimera: Collaborative Preemption for Multitasking on a Shared GPU
Chimera: Collaborative Preemption for Multitasking on a Shared GPU
by holly
Jason Jong Kyu Park. 1. , . Yongjun. Park. 2. , a...
CPUs, GPUs, accelerators and memory
CPUs, GPUs, accelerators and memory
by joanne
Andrea Sciabà. On behalf of the Technology Watch ...
Tingjun  Yang, Maria Acosta, Phil Harris, Ben Hawks, Burt Holzman, Jeff Krupa, Kevin Pedro,
Tingjun Yang, Maria Acosta, Phil Harris, Ben Hawks, Burt Holzman, Jeff Krupa, Kevin Pedro,
by finley
Nhan. Tran, Mike Wang. Neutrino Physics and Machi...
CS 732: Advance Machine Learning
CS 732: Advance Machine Learning
by jade
Usman Roshan. Department of Computer Science. NJIT...
1 Lecture: 3D CNNs, Gradient Compression
1 Lecture: 3D CNNs, Gradient Compression
by ella
Topics: . Diffy. , Morph, Gradient Compression. 3D...
[PDF]-GPU Zen 2: Advanced Rendering Techniques
[PDF]-GPU Zen 2: Advanced Rendering Techniques
by kinnickbladen
The Desired Brand Effect Stand Out in a Saturated ...
[READING BOOK]-GPU Zen: Advanced Rendering Techniques
[READING BOOK]-GPU Zen: Advanced Rendering Techniques
by gersontaniish
The Desired Brand Effect Stand Out in a Saturated ...
[BEST]-GPU Zen 2: Advanced Rendering Techniques
[BEST]-GPU Zen 2: Advanced Rendering Techniques
by janoahjamaahl
The Desired Brand Effect Stand Out in a Saturated ...
[DOWLOAD]-GPU Zen: Advanced Rendering Techniques
[DOWLOAD]-GPU Zen: Advanced Rendering Techniques
by janoahjamaahl
The Desired Brand Effect Stand Out in a Saturated ...
Nov 19, 2018 Xi Chen  University of Kentucky
Nov 19, 2018 Xi Chen University of Kentucky
by AngelEyes
Lexington, Kentucky . Gregory Gutmann . Tokyo Inst...
Training DNNs with up to 5x less memory via optimal tensor
Training DNNs with up to 5x less memory via optimal tensor
by SunnySeahorse
rematerialization. Paras Jain. Joint work with: . ...
GPU and machine learning solutions for comparative genomics
GPU and machine learning solutions for comparative genomics
by CottonTails
Usman Roshan. Department of Computer Science. New ...
Intelligent trigger for Hyper-K
Intelligent trigger for Hyper-K
by julia
Akitaka Ariga. University of Bern, Switzerland. Re...
Genome alignment Usman Roshan
Genome alignment Usman Roshan
by okelly
Applications. Genome sequencing on the rise. Whole...
CombiningendoscopicultrasoundwithTimeOfFlightPETTheEndoTOFPETUSProj
CombiningendoscopicultrasoundwithTimeOfFlightPETTheEndoTOFPETUSProj
by scarlett
Contentslistsavailableatjournalhomepagewwwelsevier...
MODALITES DE RECLAMATION DES FACTURES AU GROUPE PUBLIC UNIFIE
MODALITES DE RECLAMATION DES FACTURES AU GROUPE PUBLIC UNIFIE
by victoria
SERVICE ASSISTANCE FACTURES FOURNISSEURS MARS 2020...
29 2018  Silicon Valley
29 2018 Silicon Valley
by eleanor
March 26 - * CUDA Learning Environment Steven Dalt...
CTO, SK Telecom
CTO, SK Telecom
by oneill
“NUGU ” SK Telecom AI Assistant 2017. 2. 27...
corestoaGraphicsProcessingUnit(GPU),andweusetheGPUtorunourracedetectio
corestoaGraphicsProcessingUnit(GPU),andweusetheGPUtorunourracedetectio
by messide
AlgorithmRecordEvent(e)(Executedbyapplicationthrea...
Aho-Corasick  String  Mataching
Aho-Corasick String Mataching
by leventiser
on Shared and Distributed-Memory Parallel Architec...
A Scalable Heterogeneous Parallelization Framework for
A Scalable Heterogeneous Parallelization Framework for
by mercynaybor
Iterative Local Searches. Martin . Burtscher. 1. ...
A Scalable Heterogeneous Parallelization Framework for
A Scalable Heterogeneous Parallelization Framework for
by pinperc
Iterative Local Searches. Martin . Burtscher. 1. ...
Triggering Events with GPUs at ATLAS
Triggering Events with GPUs at ATLAS
by bikersphobia
S. Kama. , . J. Augusto . Soares. , J. . Baines, M...
PA0 – Hello CUDA CUDA Compute Unified Device Architecture
PA0 – Hello CUDA CUDA Compute Unified Device Architecture
by bubbleba
Defines much more than an API. A language . Hardwa...
CUDA - 101 Basics Overview
CUDA - 101 Basics Overview
by broadcastworld
What is CUDA?. Data Parallelism. Host-Device model...
State of CyberGIS Shaowen Wang
State of CyberGIS Shaowen Wang
by dailyno
CyberInfrastructure and Geospatial Information Lab...
CS 179 Lecture 6 Synchronization, Matrix Transpose,
CS 179 Lecture 6 Synchronization, Matrix Transpose,
by mastervisa
Profiling, AWS Cluster. Synchronization. Ideal cas...
Energy-Efficient Data  Compression for Modern Memory Systems
Energy-Efficient Data Compression for Modern Memory Systems
by katrgolden
Gennady Pekhimenko. ACM Student Research Competiti...
RIDOS Simona Giordanengo
RIDOS Simona Giordanengo
by shangmaxi
INFN Torino. Comparison. FFP1 «. measured. » dos...
Acceleration of Frequent
Acceleration of Frequent
by welnews
Itemset. Mining on FPGA Using . SDAccel. and . V...
RASFX: A VLBI GPU-based software
RASFX: A VLBI GPU-based software
by medshair
correlator. Voytsekh Ken. Igor . Surkis. Dmitry Pa...
Piko : A  Framework for
Piko : A Framework for
by eatsyouc
Authoring Programmable . Graphics . Pipelines. Anj...
Evaluating Coprocessor Effectiveness for DART
Evaluating Coprocessor Effectiveness for DART
by narrativers
Ye . Feng. SIParCS. UCAR/NCAR Boulder, CO . Univer...
µ C-States: Fine-grained GPU
µ C-States: Fine-grained GPU
by olivia-moreira
µ C-States: Fine-grained GPU Datapath Power Ma...
CS 179: GPU Computing
CS 179: GPU Computing
by debby-jeon
CS 179: GPU Computing Lecture 18: Simulations and...
Hoda   NaghibiJouybari
Hoda NaghibiJouybari
by jane-oiler
Hoda NaghibiJouybari Khaled N. Khasawneh an...