GPU Architectures &

Computing

VU Ezio  Bartocci  

Vienna  University  of  Technology  

Overview •  ECTS: 6.0 •  Web: http://ti.tuwien.ac.at/cps/teaching/courses/gpu_architectures_and_computing/

•  Lecturer: Ezio Bartocci •  Lectures: Tuesday/Thursday 10-12 am •  Institute: E182 Institute of Computer Engineering (Library - 3rd Floor) •  Language: English •  Enrollment Deadline: 7 March •  Prerequisites:

•  VU Algorithmen und Datenstrukturen 1 •  VU Algorithmen und Datenstrukturen 2 •  182.695 LU Digital Design and Computer Architecture •  182.709 UE Operating Systems •  351.015 VU Signals and Systems 1 •  389.055 VU Signals and Systems 2

Aim of the course The objectives of this course are:

•  gaining understanding of GPU computer architecture

•  getting familiar with GPU programming environments

•  Implementing programs solving problmes that would classically have been run on supercomputers

The requirements for this course are:

•  Basic notions of Computer Architecture

•  Good knowledge of C/C++ programing is expected

Main Topics

The main topics of the course are:

•  GPU Architectures

•  CUDA Programming Model

•  OpenCL Programming Model

•  GPU Computing: Case Studies

•  Optimizing GPU performances

Our equipment (1)

Our Rack is now equipped with:

•  4 NVIDIA Kepler K10

•  8 GPU with 12288

•  16 Teraflops in sigle precision

•  1 Teraflops in double precision

•  64 GB of RAM available on CPU •  32 GB of RAM available on GPU

Our equipment (2)

NVIDIA Carma (2):

•  Tegra 3 quad-core ARM A9 processor,

•  Quadro 1000M GPU with 96 cores (good for 270 single-precision GFlops)

•  one Gigabit Ethernet interface

EMBEDDED  SOLUTION  

Some GPU Applications

3D  Model  of  a  Pig  Heart  (Fenton-­‐Karma  3V  Model)  

3D  Model  of  a  Mouse  Heart    (Fenton-­‐Karma  3V  Model)  

Minimal  Model  in  Four  State  Variables  (4V)  

Suggested Books CUDA  by  Example:  An  IntroducPon  to  General-­‐Purpose  GPU  Programming  Jason  Sanders,  Edward  Kandrot,  Addison  Wesley  

Programming  Massively  Parallel  Processors:  A  Hands-­‐on  Approach  David  B.  Kirk,  Wen-­‐mei  W.  Hwu,  Morgan  Kaufmann  

CUDA  ApplicaPon  Design  and  Development  Rob  Farber,  Morgan  Kaufmann  

GPU  CompuPng  GEMS  Emerald  EdiPon  Wen-­‐Mei  w.  Hwu,  Morgan  Kaufmann  

Heterogeneous  CompuPng  with  OpenCL  Benedict  Gaster,  Lee  Howes,  David  R.  Kaeli,  Perhaad  Mistry,  Dana  Schaa,  Morgan  Kaufmann  

Suggested Books

Grading

•  Student Presentation 30%

•  Lab Protocol 20% •  Code 50%