Recent news

Science Award 2010 sponsored by the Tyrolean Chamber of Trade, Commerce and Industry

Dec 29, 2010

Herbert Jordan MSc, member of the research group DPS (Distributed and Parallel Systems) at the Institute of Computer Science, was awarded the Science Award, sponsored by the Tyrolean Chamber of Trade, Commerce and Industry on 15. December 2010. ... More

Ongoing Projects

KineControl

One of the major problems in the practical application of industrial robots is the high effort which results from revising the handling task of the robot or from replacing the robot by different type. The main reason is the complex relationship between the movement to be performed by the robot, and the required movement of each of the robots axes, the so called inverse kinematics of the robot. It is a non-linear mathematical problem with no unique solution. Basic research at the Department of Geometry and CAD at the University of Innsbruck yielded a general algorithm for solving the inverse kinematics.


It is critical, in particular for mobile robots, that the algorithm is executed in real time within the robot controller as quickly as possible. The DPS group is investigating fundamental strategies of parallelizing the algorithm and developing parallel implementations on multiprocessor systems and multicore architectures. Possibilities for parallelism in the calculations will be evaluated and exploited. In addition, we are exploring implementations of the method not only in software, but also in hardware, by employing the potential of field programmable gate arrays (FPGAs) for use in high performance computing.

The project has been started in October 2010.

Project partners:
UMIT, Institute of Automation and Control Engineering (Prof. Michael Hofbaur):

  • modular robot test bed, specifications of criteria for path planning, numerical studies, experimental evaluation

LFUI, Department of Geometry and CAD of the Faculty of Civil Engineering (Prof. Manfred Husty):

  • algorithmic formulations of inverse kinematics and optimal path planning

LFUI, Institute of Computer Science, Department of Distributed and Parallel Systems (Prof. Thomas Fahringer):

  • parallel implementation of the kinematic engine


Project Homepage:
http://www.umit.at/page.cfm?vpath=departments/technik/iace/research/kinecontrol

Article in "Der Standard":
http://derstandard.at/1291454233140/Vom-Fliessbandsklaven-zum-flexiblen-Roboter

 

RainCloud: Scientific Computing in the Cloud, Standortagentur Tirol

Despite the existence of many vendors that, similar to Grid computing, aggregate a potentially unbounded number of compute resources, Cloud computing remains a domain dominated by business applications (e.g. Web hosting, database servers) and whose suitability for scientific computing remains largely unexplored. In this project we plan to research basic methods that investigate the potential of Cloud infrastructures for high-performance scientific computing and apply them for operational daily use in a domain with high computational and QoS demands: meteorological weather forecast.

Project objectives:

  • Investigate the performance of the computational resources offered by commercial Cloud providers and device models that assess whether their performance is sufficient for scientific computing;
  • Research resource management and scheduling methods for scientific workflows on Cloud platforms by extending an existing Grid application development and computing environment;
  • Research economically-viable SLAs that encapsulate a balance between the QoS offered by the resource providers and the cost of resource use;
  • Quantify the benefits of using leased Cloud resources for scientific applications with respect to performance, reliability, and price, compared to traditionally owned supercomputers, clusters, and Grids;
  • Validate the research methods for two real scientific applications from the meteorological and astrophysics domains;
  • Use the researched methods and infrastructure in operational daily use at the Avalanche Service Tyrol and the Tyrolean Hydrographical Service for obtaining precipitation forecasts in mountainous terrains with a spatial resolution of 0.5 km and with extensive information about the uncertainty of the forecasts.

Benefits of this project:

 

For University Innsbruck

The results from this project can represent essential input for the University of Innsbruck in shifting its business model from operating an expensive self-owned data/supercomputing centre towards renting on-demand resources from specialised companies in the right amount only when and for how long it is needed. Through this ability, University of Innsbruck can avoid capital expenditure on hardware (operation, maintenance, and over-provisioning), software, and services, rather paying a provider only for what they use. Consumption is billed on a utility (e.g. resources consumed, like electricity) or subscription (e.g. time-based, like a newspaper) basis with little or no upfront cost. By combining a professionally run data centre with an economy of scale, Clouds promise to become a cheap alternative to supercomputers and specialised clusters, a much more reliable platform than Grids, and a much more scalable platform than the largest of commodity clusters or resource pools. This new paradigm can produce significant budget savings which can be redirected by the University of Innsbruck towards the real science (e.g. hiring additional research stuff) rather than investing on non-profitable infrastructure hardware.

 

For Tirol Region
Two public services, which provide a user platform for the meteorological application of this project, will already test the product during its development phase:

  1. The daily avalanche bulletin of the Avalanche Service Tyrol (Lawinenwarndienst, LWD) has a huge potential impact on day-to-day operations of ski areas,  tourism centres, and everyday live throughout Tirol in winter, e.g. through road blocks, necessary avalanche blasting, etc. The LWD product is based on automatic and human observations, as well as numerical weather forecasts. Providing additional support with probability information helps to make the decisions and forecasts more precise. The LWD needs twice-daily updated visualization in a user friendly manner of the precipitation fields as well as the computed and simulated certainties/uncertainties. All this information has to be available before a specific time each day, as the LWD outputs its avalanche bulletin at 7:30 AM;
  2. The Tyrolean Hydrographical Service (Hydrographschen Dienst) has among many duties the warning of risks of flooding and landslides. Especially for extreme precipitation events with low recurrence periods, having additional fine-scale probability information about the expected amounts instead of just one (or a few) precipitation sums is very helpful. It can support emergency services for prevention measures and planning in case of such an event

On-Demand Resource Provisioning for Online Games, Austrian Science Fund (FWF)

 Online entertainment including gaming is a strongly growing sector worldwide. Massively Multiplayer Online Games (MMOG) grew from 10 thousand subscribers in 1997 to 6.7 million in 2003 and the rate is accelerating estimated to 60 million people by 2011. Today’s MMOGs operate as client-server architectures, with server Hosters providing a large static infrastructure with hundreds to thousands of computers for each game in order to deliver the required Quality of Service (QoS) to all the players. Since the demand of a MMOG is highly dynamic, a large portion of the resources is unused most of the time, even for large providers that operate several game titles in parallel. This inefficient resource utilisation has negative economic impacts by preventing any but the largest hosting centres from joining the market and dramatically increases prices.


Today, a new research direction coined by the term Cloud computing proposes a cheaper hosting alternative by leasing virtualised resources large specialised data centres only when and for how long they are needed, instead of buying expensive own hardware with costly maintenance and fast deprecation. Despite the existence of many vendors that aggregate a potentially unbounded number of resources, Cloud computing remains a domain dominated by Web hosting or data-intensive applications, and whose suitability for computationally-intensive applications remains largely unexplored.


In this project we propose to conduct basic research that investigates new generic Cloud computing techniques to support QoS-enabled resource provisioning for computationally-intensive real-time applications by investigating:

  • Performance models for virtualised Cloud resources, including characterisation of the Cloud virtualisation and software deployment overheads;
  • Proactive dynamic scheduling strategies based on QoS negotiation, monitoring, and enforcement  techniques;
  • SLA provisioning models based on an optimised the balance between risks, rewards, and penalties;
  • Resource provisioning methods based on time/space/cost renting policies, including a comparative analysis between Cloud resource renting and conventional parallel/Grid resource operation;

Our ultimate goal is to apply and validate our generic methods to MMOGs, as a novel class of socially important applications with severe real-time computational requirements to achieve three innovative objectives:
Improved scalability of a game session hosted on a distributed Cloud infrastructure to a larger number of online users than the current state-of-the-art (i.e. 64 - 128 for FPS action games);

  • Cheaper on-demand provisioning of Cloud resources to game sessions based on exhibited load;
  • QoS enforcement with seamless load balancing and transparent migration of players from overloaded servers to underutilised ones within and across different Cloud provider resources.

Static & Dynamic Multi-objective Optimizations for Many-core Chips

For the duration of a two year project with Intel, the Distributed and Parallel Systems Group got access to a new and experimental multicore chip, the Single-chip Cloud Computer (SCC).

The aim of the project is to study the effect of modifications in the program code being executed as well as modifications of the hardware on runtime, power and energy consumption, as well as other non-functional parameters that are of interest. In addition, research regarding the automatic, simultaneous optimization of multiple, different objectives (multi-objective optimization) will be done. Such optimization strategies facilitate the development of software for multicore architectures since it requires less knowledge about parallel programming while still offering the vast performance that is potentially available in hardware.

The Intel SCC offers new possibilities, consisting of 48 cores that are interconnected via a high performance on-chip network. Primarily intended as a research object for parallel computing, it contains further distinguishing elements such as separate communication buffers that speed up communication between the cores. In addition to the high number of cores and its special architecture, it differs from other current multicore processors by providing new energy management functions. They enable the developer to change the operating frequency and voltage of groups of cores and therefore offer fine-grained power and energy consumption optimization capabilities with regard to the current work load. Furthermore previously unknown hardware optimization techniques are made available with the chip's highly configurable architecture.

With these properties and the trend of increasing numbers of cores in future processors, the Intel SCC represents an interesting chip for research in the field of non-functional parameter studies and multi-objective optimization.

SHIWA - SHaring Interoperable Workflows for large-scale scientific simulations on Available DCIs

The SHIWA project's main goal is to leverage existing workflow based solutions and enable cross-workflow and inter-workflow exploitation of DCIs by applying both coarse- and fine-grained strategies.

The coarse-grained (CG) approach enables to combine workflows written in different workflow languages in order to reuse existing reuse and combine existing workflow applications written in various workflow languages. The CG approach treats existing workflows as black box systems that can be incorporated into other workflow applications as workflow nodes. The fine-grained approach addresses language interoperability by defining an intermediate representation to be used for translation of workflows across various systems (ASKALON, Pegasus, P-Grade, MOTEUR, Triana). SHIWA develops, deploys and operates the SHIWA Simulation Platform to offer users production-level services supporting workflow interoperability following both approaches. As part of the SHIWA Simulation Platform the SHIWA Repository facilitates publishing and sharing workflows, and the SHIWA Portal enables their actual enactment. Use cases targeting various scientific domains will serve to drive and evaluate this platform from a user's perspective.The SHIWA project started on the 1st of July 2010 and lasts two years. Official website here.

 

Doctoral School (FWF DK-plus):Computational Interdisciplinary Modelling

The Doctoral School “Computational Interdisciplinary Modelling” initiated by the University of Innsbruck brings together leading scientists from various fields: applied and basic research areas from astro-, plasma, and molecular physics and engineering on one hand and the methodologically oriented fields mathematics and computer science on the other hand. Apart from interdisciplinarity, an innovative teaching concept combined with strong international networking are key to this programme. The project is funded by the Austrian Science Fund FWF and the University of Innsbruck for a period of up to 12 years.

More infos here and DPS related projects here.

 

OpenCore:

A ManyCore Compiler for Industrial Engineering Stability Analysis

This project aims at solving the computationally-intensive nonlinear structural analysis problem of large and complex light weight structures by using modern parallel multi-core processors enhanced with hardware accelerators such as e.g. GPUs. The project therefore addresses the following two research gaps.

On the one hand, the structural response of lightweight structures is characterised by the occurrence of bifurcation points which determine the load carry capacity. A rigorous treatment of the load carrying behaviour of complex structures consists of three steps: (1) exact localisation of bifurcations in course of the equilibrium path continuation; (2) classification of the singularity and determining the direction(s) of the bifurcated branch(es); and (3) choosing a predictor for initialising the path following procedure in the post-buckling regime. While steps 1 and 2 are well understood from a mathematical point of view, step 3 relies essentially on engineering decisions. However, a reliable and robust assessment of highly loaded, imperfection-sensitive structures is still a challenging problem for the engineer applying commercial finite element programs. The nonlinear analysis of complex lightweight structures like the Front Skirt of the ARIANE 5 launcher with three million degrees of freedom requests a huge computing time. The detection of critical domains within the structural response claims a large part of the computing time using currently available commercial Finite Element Method (FEM) software like ABAQUS or ANSYS.

On the other hand, processor development encountered the three walls for serial performance: the power wall, the memory wall, and the instruction-level parallelism wall. This led to CPUs aggregating multiple processing cores as well as specialized hardware accelerators with very high peak performance gained though their massively parallel architecture. Unfortunately, each of these new devices is offering a different programming interface and execution environment which hinder applications from being ported to different platforms and make the joint use of different tightly-coupled multi-core devices difficult or impossible..More Infos here...

 

CloudComputing

The Cloud Computing paradigm holds good promise for the performance hungry scientific community. Clouds promise to be a cheap alternative to supercomputers and specialized clusters, a much more reliable platform than grids, and a much more scalable platform than the largest of commodity clusters or resource pools. More Infos here...

HiPEAC

is a European Network of Excellence on High Performance and Embedded Architecture and Compilation, funded by the Computing Systems research objective of the European FP7-ICT programme

This network coordinates nine research clusters that will explore on-chip multi-cores technology and customisation, leading to heterogeneous multi-core systems. HiPEAC's main objective is to harmonise European research efforts in the area of computer systems by developing a common research vision, as well as organising meetings at regular intervals and stimulating European co-operation.

The research clusters focus on the following areas:

  • multi-core architecture;
  • programming models and operating systems;
  • adaptive compilation;
  • interconnects;
  • reconfigurable computing;
  • design methodology and tools;
  • binary translation and virtualisation;
  • simulation platform;
  • compilation platform.

Research in computer systems finds itself at a turning point, project partners state: more and more, the supercomputer market, the commodity market, including laptops and other consumer electronics such as mobile phone, PDAs and navigation systems and the embedded market are interconnected. Increasingly, the same components are used in all of these systems, creating new business opportunities for the European computer industry.

Yet innovation in the field of high-performance processors is subject to physical limitations. As a result, these processors shifted towards parallelism, using multi-core systems, so that many instructions can be carried out simultaneously. While in theory this shift to parallel computing will increase performance and cut energy consumption at the same time, multi-core structures create new problems for computer architects.

The activities envisioned in the network 'will lead to the permanent creation of a solid and integrated virtual centre of excellence consisting of several highly visible departments, and this virtual centre of excellence will have the critical mass to really make a difference for the future of computing systems,' the project partners believe.

Between 2008 and 2011, the HiPEAC consortium will receive €4.8 million under the Seventh Framework Programme (FP7). The group of Prof. Thomas Fahringer, Inst. of Computer Science, University of Innsbruck participates as a HiPEAC member (as of May 2009) in the research areas: programming models, compilers, tools as well as contributes to the ROADMAP and the task force on applications.

More information can be found at http://www.hipeac.net.

Parallel Computing with Java for Manycore Computers

In a few years from now most mainstream processors will be equipped with more than 100 cores (chip-level multiprocessors) and the number of cores will double approximately every 1,5 years. Such processors are commonly known as manycore processors. Every desktop computer, server, supercomputer, cell phones, game console (with the Playstation 3 as a prominent representative), notebook, PDA (personal digital assistant) will be based on manycore processors which will be a fundamental turning point for computer architecture and software development. All applications used in industry, commerce, science, entertainment, education and private sectors will have to be parallel and should behave well in ranges between 100 and 10000 cores. Many applications and algorithms will have to be restructured (in many cases at best semi-automatically) if those applications should progress at the same speed as the hardware (increase of cores per processor) is progressing.

The goal of this project is to provide a novel development environment for Java programs that will run on manycore parallel architectures which will cover a wide variety of computers including desktop computers, servers, supercomputers, cell phones, game consoles, notebooks, and PDAs. As part of this project we plan to develop a programming paradigm that allows a programmer to control parallelism, load balancing and locality at a high level of abstraction, and a measurement and instrumentation framework to analyse Java programs.
 

More information can be found at project home web site.

The duration of this project is 3 years. It will start in Dec. 2008 and is funded by the Tiroler Zukunftsstiftung.

 

ASKALON

ASKALON is a programming environment for Cluster and Grid Computing. ASKALON provide tools for:

 

  • automatic performance bottleneck analysis
  • performance modeling and prediction
  • performance instrumentation, measurement, and analysis
  • a Java-based coordination and visualization system

Austrian Grid

The goal of the AUSTRIAN GRID is to start and support grid computing in Austria in general, and to provide coordination and collaboration between research areas interested in grid computing.

In concrete, the AUSTRIAN GRID initiative aims at

 

  • development and usage of grid computing infrastructures for diverse application areas, and
  • installation and operation of a national grid testbed in Austria.

 

As decided on the 1st technical meeting for Austrian Grid (04 december 2003), you can find the following information about:

 

EGEE (Enabling Grids for E-sciencE)

The Enabling Grids for E-sciencE project brings together scientists and engineers from more than 240 institutions in 45 countries world-wide to provide a seamless Grid infrastructure for e-Science that is available to scientists 24 hours-a-day. Conceived from the start as a four-year project, the second two-year phase started on 1 April 2006, and is funded by the European Commission.

Expanding from originally two scientific fields, high energy physics and life sciences, EGEE now integrates applications from many other scientific fields, ranging from geology to computational chemistry.
Generally, the EGEE Grid infrastructure is ideal for any scientific research especially where the time and resources needed for running the applications are considered impractical when using traditional IT infrastructures.

The EGEE Grid consists of 41,000 CPU available to users 24 hours a day, 7 days a week, in addition to about 5 PB disk (5 million Gigabytes) + tape MSS of storage, and maintains 100,000 concurrent jobs. Having such resources available changes the way scientific research takes place. The end use depends on the users' needs: large storage capacity, the bandwidth that the infrastructure provides, or the sheer computing power available.

The Distributed and Parallel Systems group of the University of Innsbruck has been a member of the EGEE-I (2004-2006), and EGEE-II (2006-2008) projects, and is currently participating in EGEE-III (2008-2010). We sharing our expertise in project porting, grid site administration, and Grid training.  

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