A 2-Day intensive GPU Programming Course


These sessions were arranged to introduce CUDA programming language to HPC users. CUDA is used to write fast numeric algorithms for NVIDIA graphics processors (GPUs). The sessions mainly focused on the basic usage of the language, exploitation of the most important features of the device (massive parallel computation, shared memory, texture memory) and efficient usage of the hardware to maximize performance. An overview of the available development tools and the advanced features of GPUs were also covered.

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Event : GPU Programming using CUDA, OpenACC and PGI .
Date : February 3rd and 4th, 2016
Time : 9.30 am to 3.30 pm
Location : Building 14, Room 111.
Speaker : Dr. Ahmed El-Mahdy, Associate Professor, E-JUST.

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Biography of Instructor: Dr. Ahmed El-Mahdy obtained his Ph.D. in 2001 from the University of Manchester, England. Then for a year he worked as a Research Associate at the Advanced Processing Technologies Group, Department of Computer Science, University of Manchester. From year 2002 till 2012 he worked as an Assistant Professor at Alexandria University. In year 2012 he was promoted to the level of Associate professor and currently he is working as an Associate Professor at the Computer Science and Engineering, Egypt-Japan University of Science and Technology, and Associate Professor at CSE, Alexandria University. His research interests include multicore architecture, analytical performance modelling, dynamic compilation, architectural support for multimedia applications, GPUs, high performance computation unconventional HPC on mobiles phone, using mobile GPUs and cloud computing. He has a number of publications in top journals and conferences in these fields. Dr. Ahmed was also awarded the prestigious IBM Faculty Award for developing analytical performance models for the Cell processor.

Following are the sessions that were covered in the workshop with links to download respective material:

1.

Introduction to GPU Programming

Download

2.

Profiling & Shared Memory in CUDA

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3.

Real Application Example: Molecular Visualization & Analysis

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4.

Introduction to OpenACC

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5.

Introduction to Thrust library for CUDA based on STL

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6.

Application Case Study of Advanced MRI Reconstruction

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7.

PGI Compiler User's Guide

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8.

Facial Recognition System Using Embedded GPUs

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9.

Controlled Optimization of Traffic Phases

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