Das HPC Ökosystem in Darmstadt und Hessen

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1 Das HPC Ökosystem in Darmstadt und Hessen Christian Bischof FG Scientific Computing Hochschulrechenzentrum Technische Universität Darmstadt ZKI AK Supercomputing C. Bischof 1

2 The HPC Ecosystem Hardware: A HPC system Infrastructure: A building, electricity, cooling Operational staff: To make sure the base system is running Often, this is as far as it goes, and there is no money left for Software: Application packages and tools that cost money User support: Staff who advises users on, for example, the scheduling system Application support: Staff who supports users in getting their codes to perform well If this is so, this is shortsighted!! 2

3 Total Cost of Ownership (TCO) for HPC Service (Experiences at RWTH Aachen University through 2010) Assumptions 2 Mio HW investment per year 5 years lifetime with 4 years maintenance (10% of invest) through vendor 850 KW, PUE=1.5, 0.14 per kwh => 1.5 Mio per year ISV software provided by users Commercial batch system Free Linux distribution 4 FTE are for brainware (see later) costs per year percentage Building ( 7.5Mio / 25y) % Investment compute servers % hardware maintenance % Power % Linux 0 0% Batch system % ISV software 0 0 % HPC software % Staff 12 FTE % Sum % 3

4 Usage Profile 100,00% 90,00% 80,00% 70,00% 60,00% 50,00% 15 projects consume half the cycles! 40,00% 30,00% 20,00% 10,00% 0,00% Accumulated usage of top accounts 4

5 Let s see what an HPC expert can do Assumptions: An expert takes 2 months to tune a project. An expert can tune 5 projects per year. A project profits for 2 years. So on average an expert can take care of 10 projects per year. An expert costs 60,000. Tasks include, for example: Tuning, mapping, libraries, compilers. Cache, Vectorization, OpenMP, MPI, CUDA/OpenCL optimization. Hybrid parallelization. 5

6 Return on Investment (5/10/20 Percent Improvement) Cost neutral: Hiring of 7,5 HPC specialists, if they improve performance of the top 75 projects by 10% ROI [ ] #Projects Brainware for Green HPC, C. Bischof, D. an Mey, C. Iwainsky, in Proc. Int. Conf. on Energy Aware High Performance Computing 2011 (ENA HPC2011), Th. Ludwig, Ed., appeared in series Computer Science Research and Development, Springer Verlag, # tuned projects One FTE ( /year) handles 10 projects. 6

7 Green IT and Green software Green IT seems focused on energy consumption, in particular in regards to exascale. If PUE drops from 1,5 auf 1,0, this saves approx. 0.5 Mio EUR/year (corresponding to 10% of total cost). The Linpack benchmark becomes increasingly irrelevant as a predictor of real workload performance. In my experience, often the sustained performance of real HPC workloads is low. If there are no people resources available to ensure that codes perform reasonably well on our platforms, we waste serious money!!! 7

8 The Software Gap Parallel programming is intellectually challenging. The low level of abstraction offered by today s prevalent parallel computing standards does not ease the complexity and encourages programming towards a particular architecture. The software gap: Today s CSE ecosystem is unbalanced, with a software base that is inadequate to keep pace with evolving hardware and application needs Presidents Information Technology Advisory Committee - Report to the President 2005: Computational Science: Ensuring America s competitiveness 8

9 Productivity versus Performance Traditionally, HPC programming has been slanted towards performance heroic programmers getting good performance on their machine. In the future, productivity is much more important, i.e. how long does it take for a scientist to express his ideas in a code that is correct makes sensible use of HPC resources, and can be maintained over a series of architectures. 9

10 Two approaches to closing the software gap 1) Investing in HPC software stewardship: Provide brainware, i.e. HPC experts that regularly adapt codes to changing HPC environments. That is, software, like hardware, is viewed as an infrastructure that is continually cared for. 2) Increasing the productivity of programming, e.g. through automation This is a different talk. 10

11 TU Darmstadt has a strong HPC research presence 4 professorships in computer science related to HPC: Bischof Scientific Computing Gösele - Graphics, Capture and massively parallel Computing Koch Embedded Systems and Applications N.N. - Parallel Programming Programs bridging the gap between modelling, numerics, sofware and application competence, e.g. Graduate School Computational Engineering Cluster Smart Interfaces Darmstadt Graduate School of Energy Science and Engineering 11

12 Brainware Brainware = HPC experts that maintain software in light of changing operating conditions. Brainware is needed to maintain software as an infrastructure. Brainware is the key to sustained performance. Brainware must be part of a sensible HPC ecosystem. An example of institionalized brainware is the HECToR Computational Science & Engineering Service in the UK. 12

13 HECToR Computational Science & Engineering Service HECTor is the UK supercomputer service (Cray XE6 System). Part of the procurement was a service to make sure that users were supported/trained in making good use of the hardware This bid was won by the Numerical Algorithms Group (NAG). Central component (staff at NAG): Advice on using the system, non-invasive tuning, profiling Distributed component (typically staff on-site): software engineering or implementation of known algorithms, not invention of new science See e.g.: DL_POLY_4 (classical MD code) 7x speed for 1 FTE, amounting to savings of over 1 Mio /yr. 13

14 Encouraging Developments Simulation labs to maintain community codes EPSRC in England: Software as an infrastructure. Recommendations of Germany s scientific council on HPC: WR-Drs-1838 (2012): Strategische Weiterentwicklung des Hoch- und Höchstleistungsrechnens in Deutschland bwhpc Spezialisierung durch Föderierung anstatt Zentralisierung auf der Tier-3 Ebene Hessisches Kompetenzzentrum für Hochleistungsrechnen 14

15 ICS2012 Brainware C. Bischof 15

16 ICS2012 Brainware C. Bischof 16

17 Das Hessische HPC Kompetenzzentrum Entwicklung eines standortübergreifenden Konzepts für: Performanz paralleler Programme Produktivität der Programmierung HPC-Softwarepflege (software stewardship) Schulungsangebot HPC-Betrieb Vermittlung der Bedeutung von HPC 8 Stellen für Hessische Universitäten (Darmstadt, Frankfurt, Gießen, Marburg, Kassel) finanziert durch Hessisches Ministerium für Wissenschaft und Kunst (HMWK) für 2,5 Jahre ab Juli 2013 mit Geschäftsstelle an TU Darmstadt. 17

18 Aufgaben des Hessischen HPC-Kompetenzzentrums Vorhandene HPC-Strukturen koordinieren, nachhaltig etablieren und weiterentwickeln. Wissenschaftler/-innen in Hessen schulen und vernetzen. Hessische HPC-Forscher bundesweit in Gremien vertreten. Das HPC-Ökosystem als Infrastruktur und Dienstleistung für die Forschung in Hessen verstetigen. Verantwortlich: C. Bischof (Darmstadt), W. Cassing (Gießen), P. Dräxler (Kassel), C. Helf (Marburg), H.-J. Lüdde (Frankfurt) 18

19 Schlußfolgerungen Software ist der Schlüssel für nachhaltige Innovation in HPC Sinnvolle Nutzung von immer mächtigeren und teureren HPC Ressourcen erfordert: Algorithmische Innovationen in den Anwendungwissenschaften und der Numerik Neue Paradigmen für Software Entwicklung, z.b. (teil-) automatisierte Code Generierung Neue Paradigmen für Software Anpassung, z.b. modell-basiertes Autotuning Finanzierung von Brainware und Anerkennung dieser Fähigkeiten als wichtige Kompetenz und beruflicher Entwicklungspfad Hessisches HPC Kompetenzzentrum ist wichtiger Schritt auf dem Weg zu einem nachhaltigen HPC Ökosystem in Hessen 19