If you are a member of the HPC community, i.e. have some experience in HPC (either in an HPC expert role at a computing centre or in a user role such as a scientist), please fill out the questionnaire below where we ask for your usage of software development best practises. Filling out the survey just takes 5 minutes:

Software Engineering for High-Performance Computing Survey

If you want to advertise the survey, below is a slide and a flyer:
Slide (PPT)
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The NordForsk-funded Nordic Center of Excellence (NCoE) eSTICC (eScience Tools for Investigating Climate Change at High Northern Latitudes) is holding a breakout session at the Arctic Circle assembly 2017 in Reykjavik. University of Iceland is a member of eSTICC and this session has been organised and is chaired by Helmut Neukirchen from the Faculty of Industrial Engineering, Mechanical Engineering and Computer Science of the University of Iceland.

This breakout session presents results from top research groups working in the fields of climate research supported by eScience, such as extensive simulations of climate change. The session takes place on Saturday, October 14th at 17:30-19:00 in room Hafnarkot on the first floor of Harpa Conference Centre. The talks can be found on the program of the Arctic Circle website and here.

Thanks to financial support from the Nordic e-Infrastructure Collaboration (NeIC) pooling competencies initiative, I am organising together with my colleagues Morris Riedel (Jülich Supercomputing centre) and Matthias Book (University of Iceland) an HPC training workshop:

The University of Iceland is offering a free cross-national training workshop on high-performance computing (HPC) and applications at the University of Iceland in Reykjavík, Iceland, 23-25 August 2017 (noon-to-noon).

This training workshop is intended for novices (such as MSc or new PhD students) as well as for more advanced HPC users from Iceland and abroad.

More information and registration on https://cs.hi.is/HPC/hpcworkshop2017.html

A general overview on the HPC activities of the University of Iceland's computer science department can be found here: https://cs.hi.is/HPC/html

A consortium including the University of Iceland participated successfully in the European Commission's Horizon 2020 research program call FET PROACTIVE – HIGH PERFORMANCE COMPUTING: Co-design of HPC systems and applications. The University of Iceland's team is lead by Helmut Neukirchen together with Morris Riedel. The secured funding for University of Iceland (387 860 EUR for three years project duration starting from 1st July 2017) will be, among others, used to hire a researcher who will perform ambitious research by providing a scientific parallel applications from the field of machine learning for extreme scale/pre-exascale high-performance computing, i.e. creating next-generation software for the next-generation supercomputing hardware.

More details can be found here.

Update on teaching: I will teach HBV101F Software Maintenance in Spring 2018 and TÖL503M Distributed Systems will be very likely taught in fall 2017 by an external teacher.

I will not be teaching in autumn 2017, hence the course HBV101F Software Maintenance and TÖL503M/TÖL102F Distributed Systems will not be taught by me. Due to lack of sufficient financing of public universities by the Icelandic government, it is currently not possible to pay someone to teach these courses. If state financing for universities improves, this might change!

Students who would have needed to take the course HBV101F Software Maintenance (which is mandatory in the Software Engineering study line) can get an exemption and take another course instead.

Some background on public university financing: in Iceland, the state spends a little bit less than 1.3 million krona (at the current exchange rate: 10 660 EUR) per student and year (which is not only for salaries of all kind of staff, but also for infrastructure such as buildings, or infrastructure to do research) whereas the average in Iceland's Nordic neighbour states is more than 2.2 million krona (at the current exchange rate: 18 000 EUR) per student and year. As a result, I am not allowed to work overtime to teach beyond my teaching obligation as I did in the past. (Well, I could work overtime, but I will not get paid and then, the state would rely on stupid professors working for free and lower the funding even further). While typically permanent overtime is more expensive than hiring additional staff, a professor has 48% teaching obligation, 12% administration and 40% research obligation. Hence, hiring a new professor just in order to add more teaching capacity, pays not off: only 48% of this salary would go into teaching. Hence, permanent working overtime of professors to ensure teaching (not talking about research -- of course, a good university needs to do both) makes in fact economically sense and is thus often the norm. Reducing funding of universities to such an extent that the only way for the universities to safe money is reducing overtime payments, therefore leads to problems with respect to teaching offerings and teaching quality! Of course, best would be instead of working and paying overtime, to employ further professors, because these ensure both teaching and research which are both pillars of universities!

If you think the underfinancing of public universities by the Icelandic government is a shame, then you have not read how University administration deals with the current underfunding of the fiscal year 2017:

Our Faculty of Industrial Engineering, Mechanical Engineering and Computer Science (Icelandic: IVT) is part of the School of Engineering and Natural Sciences (SENS or Icelandic: VoN). For determining how the budget is distributing to the individual faculties, the University of Iceland applies a distribution model ("deililíkan", see the Icelandic description in Deililíkan Háskóla Íslands -- Skýrsla til rektors -- Tillögur um breytingar og úrbætur and MPA thesis Árangursstjórnun í háskólum á Íslandi, or for English texts, section 1.5.9. of Evaluation System for Public Higher Education Institutions Description and Self‐Review -- December 9, 2016 and section 3.4 of DOI:10.13177/irpa.a.2016.12.1.9, however the formula in the latter contains some typos) that involves an allocation formula that takes (among others) the teaching (in terms of number of students) and research activities (in terms of publications and acquired funding) into account. While this is calculated individually for each faculty, the money goes not directly to each faculty, but instead SENS receives the money for all its faculties. However, this money is not forwarded by the head of SENS to the faculties according to the distribution model! Instead we (who safe money) get less and others (who do not safe money) get more (in fact, they get our money):

While our IVT faculty is, together with a smaller one, the only faculty of SENS that manages to operate within the budget of the distribution model (we even use less because we have not as much permanent positions staffed as we should -- see above), the other faculties do not, but exceed their budget. Because our IVT faculty is so good in reducing costs (for example due to do teaching as cheaper overtime -- see above), our money is taken away and given instead to all the faculties that do not manage to stay within their budget. In fact, we are even requested to save even more (see above: no overtime payments) while the other faculties are allowed to continue spending more than the budget distributed to them according to the distribution model allows.

TL;DR: we are forced by the University administration to cut down our budget far beyond our allocation ("earned" by us due to our performance indicators used as input for the distribution model) in a way that we sacrifice our teaching offering and quality -- only to feed the other faculties that need more money than according to their allocation (they either have to improve their performance indicators, convince everyone to change the distribution model, or safe money). Due to a lack of transparency, we cannot even check whether the others at least try to safe money (e.g. while we cancel courses with less than 10 participants, we do not know whether they do this at all): we were only given by the dean of SENS their overall budget need but no motivation for their budget.

I leave it up to you to decide whether this makes SENSe or not.

P.S.: In January 2017, we were not paid any overtime: this overtime payment refers to overtime worked in 2016, i.e. the word is (we were never officially informed about the reason -- see lack of transparency above) that the dean of SENS refuses to pay work the we did back in 2016 (and even earlier in some cases) even though it was not forbidden to work overtime in these days, but overtime was rather ordered. This is a clear violation of the collective wage agreements (so also the University administration relies on stupid professors working for free). At least, I get my normal fixed salary paid -- in contrast to a part time teacher who did not get paid at all unless he threatened to go on hunger strike. Maybe we should do the same...

P.P.S.: Notably, the university mastered the severe financial crash 2008 in Iceland without the above problems. It needed a new government that in times of a flourishing economy of 2016/2017 underfinances the university. That government was elected (over the one that cleaned up the mess after the 2008 crisis and allowed indebted house owners to write off debts that were higher than 110% of their property's value) because it promised even more write-offs of housing debts (which is one of the reason why that government has no money left to finance the universities). It just came into light that those that benefited most from these write offs where those with high-income that took high loans -- in contrast to those that wisely did avoid high debts or even made no debts at all. Does this remind you of the above faculties that do not stay within their budget and thus get even more money and our faculty that wisely stays withing its budget...?

Update deadline extended until 3. February 2017!

Due to the fast development of information technology, the understanding of phenomena in natural, engineer, economy and social sciences increasingly relies on computer simulations. Simulation-based analysis and engineering techniques are traditionally a research focus of Clausthal University of Technology and University of Göttingen, which is especially reflected in their common interdisciplinary research cluster "Simulation Science Center Clausthal-Göttingen". In this context, the first "Clausthal-Göttingen International Workshop on Simulation Science" aims to bring together researchers and practitioners from both industry and academia to report on the latest advances in simulation science.

The workshop considers the broad area of modeling & simulation with a focus on:

• Simulation and optimization in networks:
  Public & transportation networks, computer & sensor networks, queuing networks, Internet of Things (IoT) environments, simulation of uncertain optimization problems, simulation of complex stochastic systems
• Simulation of materials:
  Development and applications of computational techniques in material and process simulation, simulation at micro (atomistic), meso and macro (continuum) scales including scale bridging, diffusive, convective transport and chemical processes in materials, simulation of granular matter
• Distributed simulations:
  Technology enabler for distributed simulation (e.g., simulation support for vector and parallel computing architectures, grid-based systems and cloud-based systems), methods for distributed simulation (e.g., agent-based simulation, multi-level simulation, and simulation for big data analytics, fusion and mining), application examples (e.g., simulation-based quality assurance and high-energy physics)

27 - 28 April 2017, Göttingen, Germany

Extended Abstract (2-3 pages) Submission: 20 Jan 2017

Workshop web page

Call for Papers: Download

The eSTICC project is holding a session on "eScience, ensemble methods and environmental changes in high latitudes" at EGU (European Geosciences Union General Assembly) 2017 Vienna, Austria, 23-28 April 2017.

Convener: Ignacio Pisso
Co-Conveners: Andreas Stohl, Michael Schulz, Torben R. Christensen, Risto Makkonen, Tuula Aalto, Helmut Neukirchen, Alberto Carrassi, Laurent Bertino.

The multiple environmental feedback processes at high latitudes involve interactions between the land, ocean, cryosphere, biosphere and atmosphere. For trustworthy computational predictions of future climate change, these interactions need to be taken into account by eScience tools. In particular, this requires: 1) Integration of existing measurement data and enhanced information flow between disciplines; 2) Representation of the current process understanding in Earth System Models (ESMs) for which computational limitations require balancing the process simplifications; and 3) Improved process understanding. eScience such as High-Performance Computing (HPC), big data or scientific workflows is central in all of these areas.
Contributions in fields related to the intersection of environmental change (such as, but not restricted to, measurements, inverse modeling, data assimilation, process parametrizations, ESMs) and eScience (such as, but not restricted to, and HPC, scientific workflows, big data, ensemble methods) are welcome.

The session welcome contributions in fields related to the intersection of environmental change (such as, but not restricted to, measurements, inverse modeling, data assimilation, process parametrizations, ESMs) and eScience (such as, but not restricted to, and HPC, scientific workflows, big data, ensemble methods).

The deadline for receipt of abstracts is 11 January 2017, 13:00 CET. You are welcome to submit abstracts via the session's web page.

In the age of Big Data and big data frameworks such as Apache Spark, one might be tempted to think that supercomputing/high-performance computing (HPC) is obsolete. But in fact, Big Data processing and HPC are different and one platform cannot replace the other. I outline this in a presentation on Science Day of the University of Iceland's School of Engineering and Natural Sciences Saturday October 29 2016. (Note that there is nowadays some convergence, and a graph-processing benchmark top 500 list to resemble less CPU-intensive workloads in HPC.)

Furthermore, the available open-source implementations of algorithms (e.g. clustering using DBSCAN) are currently much faster in HPC and the available Big Data implementations do in fact not even scale beyond a handful of nodes. Results of a case study performed during my guest research stay at the research group High Productivity Data Processing of the Federated Systems and Data division at the Jülich Supercomputing Centre (JSC) are published in this Technical Report.

One of the reviewers of the 1st IEEE International Workshop on Big Spatial Data (BSD 2016) seems not to like the message that Big Data needs to do its homework to match HPC, hence my paper was rejected. While I assume that an HPC conference (such as ISC) might accept it, it would be nice to get the message to the Big Data community: I might submit it to The 6th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics or later at BDCloud 2017 : The 7th IEEE International Conference on Big Data and Cloud Computing. Non-public source implementations may also be worth considering: A novel scalable DBSCAN algorithm with Spark or A Parallel DBSCAN Algorithm Based on Spark. (If we get access to the implementation, but lacking possibility of reproducing/verifying scientific results is another story covered in my Technical Report.) Also, I might add threats to validity (such as construct, internal and external validity [Carver, J., VanVoorhis, J., Basili, V., August 2004. Understanding the impact of assumptions on experimental validity.])

Update from 9.11.2016: Erich Schubert (thanks!) pointed me to this related article "The (black) art of runtime evaluation: Are we comparing algorithms or implementations?" (DOI: 10.1007/s10115-016-1004-2) which support my findings. A statement from that article on k-means: "Judging from the measured runtime and even assuming zero network overhead, we must assume that a C++ implementation using all cores of a single modern PC will outperform a 100-node cluster easily." For DBSCAN, they show that a C++ implementation is one order of magnitude faster than the Java ELKI (which confirms my measurements concerning the C++ HPDBSCAN and the Java ELKI) on their used dataset. They also support my claim that the implementation matters: "Good implementations with index accelerations would process this data set in less than 2 seconds, whereas the fastest linear scan implementation took over 90 seconds, and naïve implementations would frequently require over 100 times the best runtime. But not every index we evaluated was implemented correctly, and sometimes an index was even slower than the linear scan. Between different implementations using linear scan, we can observe runtime differences of more than two orders of magnitude. Comparing the fastest implementation measured (optimized C++ code for this task) to the slowest implementation (outdated versions of Weka), we observe four orders of magnitude: less than two seconds instead of over four hours."

Fake / predatory journals (typically open access journals that publish everything as long as they get paid for it) are a problem to scholars. A good starting point to identify them is Beall’s List with lists on publishers that publish a range of fake journals, single fake journals which are not related to the above publishers, as well as hijacked journals that look like the submission web page of the original version. Also searching the above web site is a good idea.

Update from 2018: The above web pages do not exist anymore in 2018 (but 2017 versions can be retrieved via http://archive.org. In addition, there is https://beallslist.weebly.com/ that even adds new entries. Another blog covering this topic is http://flakyj.blogspot.com/.

In addition to the above blacklists, there is also some whitelist by Directory of Open Access Journals (DOAJ). But beware: some journals appear even both on the blacklist and the whitelist...

Fake / predatory conferences are also a problem, for example those hosted by IARIA: I was once myself TPC member of the The First International Conference on Advances in System Testing and Validation Lifecycle (VALID 2009). As it was the first one and even published by IEEE, it was to me at that time not obvious that this is a bogus conference. Just when I as a reviewer never got access to the reviews of the other reviewers, it became obvious that no rigorous academic standards apply and I did not anymore accept to be TPC member of any IARIA conference (nor submit there of course).

Anyway, University of Iceland respects most publications listed in ISI - Web of Knowledge and Scopus which contain so far only serious publication targets.

Even if the free Microsoft Core fonts are installed, Tahoma is missing. A Microsoft knowledge base support entry is available to download as Tahoma32.exe, however this is a broken link. Hence, download the therein contained files (tahoma.ttf and tahomabd.ttf) from elsewhere (seems to be legal as Microsoft offered them anyway to the public), e.g. https://github.com/caarlos0/msfonts/tree/master/fonts

Copy font file to ~/.fonts directory and run fc-cache -fv