Modelling & simulation

Apple vs oranges: performance comparisons

Author: Adrian Jackson
Posted: 11 Apr 2017 | 17:59

Shall I compare thee...

Performance comparisons are always tricky to get exactly right. They are needed to ensure that we can demonstrate the performance improvements that optimisations, new hardware, new algorithms, etc... have had on an application or benchmark, but there is a lot of latitude in what can be compared, which makes it easy to get a performance comparison wrong and not properly demonstrate whatever it is you're trying to show.

Work experience at EPCC

Author: Guest blogger
Posted: 10 Apr 2017 | 16:06

Guest blogger Kara Moraw is an undergraduate Informatics student in Bonn, Germany. Here she writes about her 4-week internship with EPCC, spent working with EPCC's Nick Brown on the ARCHER outreach project.

Optimised tidal modelling

Author: Adrian Jackson
Posted: 2 Feb 2017 | 11:37

Fluidity for tidal modelling

Tidal model

Figure 1: Mesh for the Sound of Islay tidal simulation. Courtesy Dr Creech.

We were recently involved in a project to optimise the CFD modelling package Fluidity for tidal modelling. This ARCHER eCSE project was primarily carried out by Dr Angus Creech from the Institute of Energy Systems in Edinburgh.

Demystifying data input to TensorFlow for deep learning

Author: Alan Gray
Posted: 29 Nov 2016 | 10:07

Shape SorterView this post on GitHub

TensorFlow is an incredibly powerful new framework for deep learning. The “MNIST For ML Beginners” and “Deep MNIST for Experts” TensorFlow tutorials give an excellent introduction to the framework. This article acts as a follow-on tutorial which addresses the following issues:

  1. The above tutorials use the MNIST dataset of hand written numbers, which pre-exists in TensorFlow TFRecord format and is loaded automatically. This can be a bit mysterious if you have no experience of data format manipulation in TensorFlow.
  2. Since the MNIST dataset is fixed, there is little scope for experimentation through adjusting the images and network to get a feel for how to deal with particular aspects of real data.

Dual-resolution simulations with LAMMPS

Author: Iain Bethune
Posted: 8 Oct 2016 | 11:46

Hierarchy of multiscale modeling

Over the last year I've been working with Prof. Jon Essex of Southampton University on an ARCHER eCSE project with the pithy title of "Implementation of Dual Resolution Simulation Methodology in LAMMPS".  

So what do I mean by dual-resolution simulations?

CP2K-UK still going strong

Author: Iain Bethune
Posted: 28 Sep 2016 | 15:06

CP2K Summer School group photoSeptember seems to have passed by in a bit of a blur, and it's already a whole month since the CP2K Summer School, which we ran at King's College London (23-26th August), so I thought it would be a good time to give an update on the recent activities of the CP2K-UK project.

Summer of HPC comes to an end

Author: Nick Brown
Posted: 2 Sep 2016 | 11:08

This week we said goodbye to our Summer of HPC students Anna, Marta and Tomislav.

These students from around Europe have spent the last 7 weeks with us at EPCC immersed in HPC, and each working on a specific project in the field. This is a great because not only do they gain experience and interest in HPC but we also get a useful, tangible, outcome from these projects.

Data and Software Carpentry combo at Edinburgh

Author: Mario Antonioletti
Posted: 29 Aug 2016 | 10:35

Software Carpentry attendees during the shell session. Pic Credit: Martin Callaghan.

With my Software Sustainability Institute hat on, I recently participated in a back-to-back Data Carpentry and Software Carpentry course sponsored by the University's Research Data Service here at the University of Edinburgh. The courses were held in the main University library in a gorgeous room with a glass wall, providing a rather distracting view of the Meadows parkland. 

Early experiences with KNL

Author: Adrian Jackson
Posted: 29 Jul 2016 | 16:45

Initial experiences on early KNL

Updated 1st August 2016 to add a sentence describing the MPI configurations of the benchmarks run.
Updated 30th August 2016 to add CASTEP performance numbers on Broadwell with some discussion

EPCC was lucky enough to be allowed access to Intel's early KNL (Knights Landing, Intel's new Xeon Phi processor) cluster, through our IPCC project.  KNL Processor Die

KNL is a many-core processor, successor to the KNC, that has up to 72 cores, each of which can run 4 threads, and 16 GB of high bandwidth memory stacked directly on to the chip.

ExTASY: a flexible and scalable approach to biomolecular simulation

Author: Iain Bethune
Posted: 18 Jul 2016 | 12:20

Over the last 10 years, the growth in performance of HPC systems has come largely from increasing core counts, which poses a question of application developers and users – how to best make use of the parallelism on offer?

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