Apr 26

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GCOE Dresden at GTC 2017

the GCOE will be present at the GPU Technology Conference (GTC) 2017, May 8-11, in Silicon Valley, organized by Nvidia. There will be more than 500 sessions during the four days, where the GCOE will participate with the following events:

High-Bandwidth 3D Image Compression to Boost Predictive Life Sciences

May 11, 10:00 AM – 10:25 AM – Room 210C
Peter Steinbach, MPI-CBG
Jeffrey Kelling, HZDR

Modern microscopes easily produce large data volumes (terabyte datasets) at high rate (1,000 megabytes/s is no exception) that makes using them almost impossible. Once an acquisition is started, it typically has to be stopped again as the hard drives run full. We’ll share how GPUs helped us bring this nightmare to an end. We’ll introduce our open-source package, called sqeazy, that is capable of compressing microscopic data at faster speeds than a hard drive can spin. We show how GPUs provided a crucial boost in this endeavor and we’ll share what technical challenges we overcame interfacing with modern video encoding libraries, like libavcodec of ffmpeg. Finally, we’ll discuss how NVENC provides portable performance that helps scientists to observe living developing specimens over long time spans. This may be the foundation for modern predictive biology of the 21st century. Join us for a tour on how modern media technology straight from Hollywood can boost science!

Efficient Correlation-Free Many-States Lattice Monte Carlo on GPUs
May 8, 2:30 PM – 2:55 PM – Room 212A
Jeffrey Kelling, HZDR

We’ll present a method for highly efficient lattice Monte Carlo simulations with correlation-free updates. Achieving freedom from erroneous correlations requires random selection of lattice sites for updates, which must be restricted by suitable domain decomposition to create parallelism. While approaches based on caching limit the number of allowed states, the multisurface-type approach presented here allows arbitrarily complex states. The effectiveness of the method is illustrated in the fact that it allowed us to solve a long-standing dispute around surface growth under random kinetic deposition in the KPZ-universality class. The method has also been applied to Potts models and is suitable for spin-glass simulations, such as those required to test quantum annealers, like D-Wave.

Multi GPU Programming with MPI and OpenACC
May 8, 12:30 PM – 2:30 PM – Room LL21E
Robert Henschel – Indiana University
Jiri Kraus – NVIDIA
Guido Juckeland – HZDR

Learn how to program multi-GPU systems or GPU clusters using the message passing interface and OpenACC. We’ll start with a quick introduction to MPI and how an NVIDIA(R) CUDA(R)-aware MPI implementation can be used with OpenACC. Other topics covered will include how to handle GPU affinity in multi-GPU systems and using NVIDIA performance analysis tools. As we’ll be using GPUs hosted in the cloud, all you are required to bring is a laptop with a modern browser. Prerequisites: C or FORTRAN, Basic OpenACC and MPI are strongly recommended but not required. This lab utilizes GPU resources in the cloud, you are required to bring your own laptop.

In-Depth Performance Analysis for OpenACC/CUDA/OpenCL Applications with Score-P and Vampir

May 10, 4:00 PM – 6:00 PM – Room LL21A
Robert Henschel – Indiana University
Jiri Kraus – NVIDIA
Guido Juckeland – HZDR

Work with Score-P/Vampir to learn how to dive into the execution properties of CUDA and OpenACC applications. We’ll show how to use Score-P to generate a trace file and how to study it with Vampir. Additionally, we’ll use the newly established OpenACC tools interface to present how OpenACC applications can be studied for performance bottlenecks. This lab uses GPU resources in the cloud, so bring your laptop. Prerequisites: Basic knowledge on CUDA/OpenACC and MPI is recommended but not required. This lab utilizes GPU resources in the cloud, you are required to bring your own laptop.

Connect with the Experts: OpenACC: Start with GPUs and Optimize Your Code
May 8, 10:00 AM – 11:00 AM – LL Pod B
May 9, 10:00 AM – 11:00 AM – LL Pod A
May 10, 1:00 PM – 2:00 PM – LL Pod C
May 11, 10:00 AM – 11:00 AM – LL Pod A
Guido Juckeland et al.

This session is designed for anyone who is either looking to start with GPUs or already accelerating their code with OpenACC on GPUs or CPUs. Join OpenACC experts and your fellow OpenACC developers to get an expert advice, discuss your code and learn how OpenACC Directives are used by others.

Permanent link to this article: https://gcoe-dresden.de/gcoe-dresden-at-gtc-2017/