'Host memory' diaporamas de présentation

CUDA Odds and Ends

CUDA Odds and Ends. Joseph Kider University of Pennsylvania CIS 565 - Fall 2011. Sources. Patrick Cozzi Spring 2011 NVIDIA CUDA Programming Guide CUDA by Example Programming Massively Parallel Processors. Agenda. Atomic Functions Paged-Locked Host Memory Streams

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KV-Direct: High-Performance In-Memory Key-Value Store with Programmable NIC

KV-Direct: High-Performance In-Memory Key-Value Store with Programmable NIC. Bojie Li 1,2 Zhenyuan Ruan 1,3 Wencong Xiao 1,4 Yuanwei Lu 1,2 Yongqiang Xiong 1 Andrew Putnam 1 Enhong Chen 2 Lintao Zhang 1 1 Microsoft Research 2 USTC 3 UCLA 4 Beihang University.

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Heterogeneous Computing: New Directions for Efficient and Scalable High-Performance Computing

Heterogeneous Computing: New Directions for Efficient and Scalable High-Performance Computing. CSCE 791 Dr. Jason D. Bakos. Minimum Feature Size. Computer Architecture Trends. Multi-core architecture:

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CUDA

CUDA. Introduction. CUDA was introduced by Nvidia in 2006 Parallel computing platform and programming model Available in several programming languages. Hardware realization. Threads are grouped in blocks Blocks are run by Streaming Multiprocessor (SM) Threads in a block run parallel

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Matthew D. Hendel Software Engineer BaseOS/Drivers

Introducing Storport. Matthew D. Hendel Software Engineer BaseOS/Drivers. Contents.

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Lecture 2: GPU History & CUDA Programming Basics

Lecture 2: GPU History & CUDA Programming Basics. Outline of CUDA Basics. Basic Kernels and Execution on GPU Basic Memory Management Coordinating CPU and GPU Execution See the Programming Guide for the full API. Basic Kernels and Execution on GPU. CUDA Programming Model.

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Portability and Performance for Visualization and Analysis Operators Using the Data-Parallel PISTON Framework

Portability and Performance for Visualization and Analysis Operators Using the Data-Parallel PISTON Framework. Chris Sewell Li-Ta Lo James Ahrens Los Alamos National Laboratory. Outline. Motivation

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VMWare ESX Memory Management

VMWare ESX Memory Management. Dr. Sanjay P. Ahuja, Ph.D. 2010-14 FIS Distinguished Professor of Computer Science School of Computing, UNF. Memory Virtualization Basics.

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VMWare ESX Memory Management

VMWare ESX Memory Management. Dr. Sanjay P. Ahuja, Ph.D. Fidelity National Financial Distinguished Professor of CIS School of Computing, UNF. Memory Virtualization Basics.

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GPU Memory Details

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OpenCL Ch. 5~7

OpenCL Ch. 5~7. Jongeun Lee. Fall 2013. Ch. 5: OpenCL C built-in functions. work-item functions math functions integer functions common functions geometric functions relational functions synchronization functions async copy and prefetch functions

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GPU programming: CUDA

GPU programming: CUDA. Acknowledgement: the lecture materials are based on the materials in NVIDIA teaching center CUDA course materials, including materials from Wisconsin ( Negrut ), North Carolina Charlotte ( Wikinson /Li) and NCSA ( Kindratenko ). CUDA.

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Heterogeneous Computing

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L17: Generalizing CUDA: Concurrent Dynamic Execution, and Unified Address Space

L17: Generalizing CUDA: Concurrent Dynamic Execution, and Unified Address Space. Administrative. Remaining Lectures Wednesday, April 17: Parallel Architectures and Getting to Exascale Final projects Poster session, April 24 (dry run April 22) Final report, May 1. Final Project Presentation.

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CUDA ????

CUDA ????. ??. ? CPU ??????? vectoradd.cu ?. #include <stdio.h> #include <stdlib.h> #include <math.h> #include <cuda_runtime.h> #include "vector_kernel.cu" #define eps 1e-9 int main ( int argc , char ** argv ) { int numElements = 50000 ;

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ODR Status 29 July 2008 Matt Warren Valeria Bartsch, Barry Green, Andrzej Miesijuk, Tao Wu

ODR Status 29 July 2008 Matt Warren Valeria Bartsch, Barry Green, Andrzej Miesijuk, Tao Wu. Hardware/Firmware. ODR is working(!) Receive data on 4x fibre (RX), Write to disk FAST (250MB) Send data up fibre (TX) Controlled from Linux driver Future upgrade: Decode event header from LDA

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