University GPU Club: Tues 23 July 2013
Software for GPUs inc. compiler/directives, maths libs & tools (debuggers and profilers)
Nearly 60 researchers and academics attended the recent meeting of the University's GPU Club to hear experts from NVIDIA and MathWorks discuss how GPUs (graphical processing units) can be used to accelerate simulations and how MATLAB's GPU-enabled functionality makes this straightforward.
MathWorks (producers of MATLAB) and NVIDIA (producers of GPUs and CUDA) presented at The University of Manchester on Tuesday 23 July on how their products can be used by UoM researchers to dramatically reduce the time to solution for their simulations.
"I came to the talks in the morning on Tuesday and I thought that they were excellent - experts that communicated well and a perfect mix of information and how to put it into practice. I haven't done any GPU computing before and it worked really well to introduce me to the subject." A.B., Centre for Imaging Sciences
Resources at Manchester IT Services
Jeremy Purches, HPC Business Development Manager, & Tim Lanfear NVIDIA
- Jos Martin, Principal Architect for Parallel Computing Tools, Mathworks.
Individual Workshops with NVIDIA and/or MathWorks (afternoon)
12 research groups met to discuss with MathWorks and NVIDIA about their research and building collaborations.
Abstracts and Speaker Biographies
NVIDIA GPU Technology
NVIDIA invented the GPU (Graphics Processing Unit) in 1999 and, starting in visual computing, have expanded into supercomputing and, most recently, into cloud computing. NVIDIA’s CUDA parallel computing platform and programming model enables dramatic increases in computing performance, while their Tesla GPU accelerators help researchers and scientists by accelerating performance and energy efficiency.
This talk will introduce the audience to NVIDIA and GPU technology, before going into more detail on future roadmaps, GPU programming, tools & management and finally application performance. The first part of the presentation will be given by Jeremy Purches, HPC Business Development Manager. Jeremy has an extensive and deep understanding of HPC having previously worked for Rolls-Royce Aero-engines, EDS and HP before joining NVIDIA. The second, more technical, part of the presentation will be given by Dr Timothy Lanfear, Senior Solutions Architect. Timothy is an acknowledged HPC industry expert with a wide and deep technical knowledge of HPC, holding a PhD from Imperial College and previous positions at Clearspeed, Hitachi, BAE Systems and NATO.
MATLAB: The challenges involved in providing a high-level language on a GPU
MATLAB provides a high-level programming language and environment that is widely used for scientific computing across academia and various industries. GPUs provide fantastic computational power in a small package for certain classes of problem. Bringing these two together allows MATLAB programmers to solve bigger problems faster, but presents a number of technical challenges.
In this talk we will look at the ways in which we have tried to provide access to the power of the GPU without requiring the user to learn new programming techniques or breaking the standard MATLAB programming model. This presents several challenges: in defining a simple interface, in reproducing answers and in keeping the GPU busy. We will discuss some of these challenges and the ways in which we have chosen to address them.
Jos Martin is the principal architect for parallel computing tools at MathWorks, leading the team that develops tools for enabling parallel computing within the MATLAB environment. Before moving to a development role, he worked as a consultant in the U.K., writing large-scale MATLAB applications, particularly in the finance and automotive sectors. Prior to joining MathWorks in 2000, he held a Royal Society Post-Doctoral Fellowship at the University of Otago, New Zealand. His area of research was Experimental Bose-Einstein Condensation (BEC), a branch of low-temperature atomic physics.
Jos holds an M.A. in physics from St. Peter’s College, University of Oxford, and a D.Phil. in atomic and laser physics from Linacre College, University of Oxford. In 2008, on behalf of MathWorks, Jos was a joint winner of the HPC Challenge Class 2 award for Most Productive Implementation at Supercomputing 08.
GPU Club Meetings
25th Nov 2014: 1.30-3.30pm, 2.220 University Place
Tues 26 Nov 2013: 2-3pm, B8 George Begg. Christian Obrecht on GPU implementations of fluid dynamics simulations on regular meshes: some recent advances
Weds 13 Nov: 2pm, Univ Place. John Michalakes (NOAA) and Craig Davies (Maxeler Dataflow)
Weds 30 Oct: Intermediate CUDA training run by NVIDIA
Tues 29 Oct: 2pm, Univ Place, NVIDIA and Stephen Longshaw.
Weds 2 Oct 2013 - Large Scale Optimization and High Performance Computing for Asset Management, Daniel Egloff (QuantAlea)
Tuesday 23 July MathWorks (GPUs for MATLAB) and NVIDIA (GPUs & CUDA)
Thur 2 May 2013 Lessons from GTC and on using the Intel Xeon Phi
Mon 10 Dec 2012 Dataflow and MultiGPU SPH
Tues 25 Sept Seminar on implementing financial models on GPUs, FPGAs and in the Cloud
Mon 15 Oct: OpenCL training from UoM IT Services
Thurs 25 Oct: Hands-on "OpenACC" workshop run by Cray UK Ltd.
17 May 2012 Speakers on healthcare policy simulation in OpenCL, MHD algorithms in CUDA, Tridiagonal Solvers in CUDA
20 April 2012 Francois Bodin, CAPS: "Programming Heterogeneous Many-Cores using Directives" using HMPP
23 March 2012 Roko Grubisic, ARM: "Embedded Computer Graphics and ARM Mali GPUs"
02 March 2012 Speakers on profiling, sparse matrix algebra and atmospheric chemistry
09 Dec 2011 MPI and GPUs, directives-based programming, FPGA and GPU comparison, ideas for 2012
30 Sept 2011 GPU programming in FORTRAN, multiple GPUs, image reconstruction
15 July 2011 Jack Dongarra key note on Emerging Technologies
18 Mar 2011 OpenCL, debugging and profiling tools, porting C to CUDA, real time analysis
26 Nov 2010 biological MD, smoothed particle hydrodynamics, Monte Carlo financial models, Markov models