Prague, Czech Republic, 10-13 September 2019

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Tools and Infrastructure for Reproducibility in Data-intensive Applications

Organisers: Sandro Fiore (Euro-Mediterranean Center on Climate Change), Ian Foster (University of Chicago), Carl Kesselman (University of Southern California)

Meaningful advances in science and engineering are increasingly predicated on data-driven decision making. For these decisions to be valid, it is essential that the one not only record the process by which the data was produced, but to actually be able to reproduce the data at every step in the process. While we are all used to tracking source code revisions, and keeping track of program inputs and outputs, the increased complexity of end-to-end computing pipelines, coupled with new big-data and machine learning algorithms, imposes significant complexity on tracking all of the steps and associated data that went into producing a result. For example, keeping track of exactly what data use used for a training set v.s an evaluation set, what cleaning was done, what analysis was done on the results to evaluate performance, and what additional experiments were performed. With the every increasing number, size, and complexity of the data used in data-intensive applications, reproducing results from these types of investigations becomes increasingly difficult. While no-one deliberately sets out to create un-reproducible results, recent surveys of the literature shows that the ability to reproduce data-intensive results are the exception and not the rule.
For these reasons, a symposium on issues, tools and infrastructure for data intensive applications is highly germane to the ParCO community. In this symposium, we propose to review current state of the art in reproducibility in data intensive computing applications. We will cover three primary topic areas:

  • Reproducibility challenges that are specific to science, engineering activities that have data intensive computing as a core aspect of the process.
  • Infrastructure, tools and methods that are currently available for reproducible data intensive applications and gaps and challenges that need to be addressed.
  • How to increase the adoption of methods for reproducible data-intensive applications across the research community.
The CFP and submission details are available on the Symposium Website.

ParaFPGA2019: Parallel Computing with FPGAs

Organisers: Erik D’Hollander (Ghent University, Belgium) and Abdellah Touhafi (Vrije Universiteit Brussel, Belgium)

ParaFPGA focuses on parallel techniques for using FPGAs as accelerator in high performance computing areas such as supercomputing, embedded systems and big data computing. Of special interest are design methods, heterogeneous architectures and algorithms optimized for execution on FPGAs. Design methods include optimizing the resource utilization, development time and high-level synthesis tools.

Heterogeneous architectures aim at multi-FPGAs, FPGAs with CPU cores and systems combining FPGAs, GPUs and CPUs. Novel algorithms optimized for FPGAs target areas such as streaming applications or fast dynamic reconfiguration, featuring a substantial performance increase. New and original contributions are invited on parallel computing with FPGAs in all areas of design methodology, performance analysis, architectures, algorithms and applications. The CFP and submission details are available on http://parafpga.elis.ugent.be.

Energy-efficient Computing on Parallel Architectures (ECO-PAR)

Organisers: Enrico Calore (INFN-Ferrara), Nikela Papadopoulou (National Technical University of Athens), Sebastiano Fabio Schifano (University of Ferrara and INFN-Ferrara), Vladimir Stegailov (HSE Tikhonov Moscow Institute)

The power requirements of large HPC facilities are becoming unsustainable for both technical and economic reasons. A significant fraction of the total cost of ownership of HPC installations available nowadays is already driven by the electricity bill, and the idea of charging users for the energy consumed by their applications is spreading.

This requires to find disruptive, smart and effective solutions, both at level of hardware and software to maximize energy-efficiency and computing throughput of HPC systems within a given power envelop.

Several recently developed processors, such multi- and many-cores CPUs, GPUs, FPGAs and SoCs (System on Chip) are engineered including features to improve computing energy-efficiency, e.g. higher level of parallelism; dynamic clock frequency adaptation; capability of switching off idle cores, etc. However, programming complexity and code portability can be affected by these choices, and computing efficiency (as well as energy-efficiency) can be disrupted if applications are not properly coded to exploit (or take into account) all of the hardware features, in the worst scenario, possibly increasing the time-to-solution and the energy-to-solution. In addition, the heterogeneity of modern compute nodes and systems, combined with the dynamic behavior of modern applications, require educated resource allocation and resource management techniques to achieve energy efficiency.

This workshop aims to strongly encourage the exchange of experiences and knowledge in novel strategies to exploit, monitor, analyze, and optimize the energy-efficiency of recent computing systems. We focus on new trends including, hardware and software tools, scheduling and resource management techniques but also algorithm-design and techniques in general, able to minimize the energy-to-solution of workloads, and to reduce the energy required to operate computing systems.

Contact the Symposium Website for further information.

ELPA - A Parallel Dense Eigensolver for Symmetric Matrices with Applications in Computational Chemistry

Organisers: Prof. Thomas Huckle (Technical University of Munich), Prof. Bruno Lang (Bergische Universitaet Wuppertal)

The Symposium is devoted to the ELPA project - an important successful parallel eigensolver for dense symmetric (Hermitian) generalized eigenvalue problems. The proposed talks will cover mathematical, algorithmical, implementational, and use-oriented aspects.

First, the mathematical approach is presented for setting up algorithms for the eigenproblem that allow efficient solution in a parallel environment, esp. the two-step approach for transforming the matrix in tridiagonal form. Furthermore, implementational details, also for the special case of banded matrices in parallel, are presented.
Then we will deal with improving the usability of the software library, esp. monitoring and autotuning tools, and optimizing the software for different parallel architectures.
Finally, the application of the solver in Computational Chemistry is presented.

Preliminary list of participants:

  • Thomas Huckle (TU Munich) and Bruno Lang (BU Wuppertal): Organisers
  • Michael Rippl (TU Munich)
  • Pavel Kus (Max-Planck-Desellschaft, Garching)
  • Christian Carbogno (Fritz-Haber-Institut Berlin)
  • Christoph Scheuerer (TU Munich).
Contact the organisers for further information.

Call for Symposia


ParCo2019 will cover the state of the art in the development, applications, and future trends in parallel computing for both High Performance (HPC) and Data Intensive Computing (DIC). Its scope encompasses all platforms, from Internet of Things (IoT) and Robotics to HPC systems, Clouds, Quantum, and Neuro-Computing.

The conference addresses all aspects of parallel computing, including applications, hardware and software technologies, and languages and development environments.


Section 1: Architectures

New concepts for parallel computing architectures for all levels of parallelism, including:

  • Multicore and manycore systems
  • Heterogeneous systems
  • Accelerators, including GPUs and FPGAs
  • High-performance systems, including peta- and exascale
  • Architectures for handling large data sets and data intensive computing, including high speed storage systems
  • Interconnection networks
  • Clouds for HPC
  • Performance evaluation
  • Energy saving designs
  • IoT and mobile devices
  • Brain-inspired systems, including neurocomputing
  • Quantum computers
  • Specialised architectures for high-performance machine learning and deep learning.

Section 2: Software

Software for parallel computing platforms, including

  • Operating systems and middleware for all types of parallel architectures
  • Software engineering methodologies, and methods and tools for developing and maintaining parallel software
  • Parallel programming languages, compilers, libraries, and environments
  • Testing and debugging techniques and tools
  • Best practices of parallel computing on multicore, manycore, and stream processors
  • Design patterns for parallel computing.

Section 3: Algorithms

Design, analysis, and implementation of parallel algorithms for all application areas, emphasising the parallel computing aspects and focusing on issues such as:

  • Scalability and speedup
  • Efficient utilization of the memory hierarchy
  • Communication and synchronization
  • Data management
  • Energy awareness.

Section 4: Applications

The application of parallel computing to solve all types of business, industrial, scientific, and engineering problems using high-performance computing technologies, in particular:

  • Astronomy and space
  • Health science and care
  • Geo- and environmental sciences
  • Computational chemistry
  • Material science
  • Bioinformatics
  • Exploration and optimal use of resources
  • Manufacturing
  • Data intensive (big data) analytics and applications
  • Economic and financial modelling
  • Learning systems (deep learning) and AI
  • Robotics
  • Automonous transport systems, including self driving vehicles
  • Virtual and augmented reality (VR and AR).

Symposium Proposals

Proposals for organising a symposium related to any of the topic areas mentioned above are solicited. Such proposals should give:

  • The proposed title of the symposium
  • The name and affiliation(s) of the organiser(s)
  • A short outline of the contents
  • The planned number of papers (preferably in the range from 3 to 10).
The organisers of symposia publish their respective calls for contributions, determine submission dates and are responsible for the refereeing and acceptance of papers.

Symposium proposals should be submitted by e-mail to the Conference Office by 31 March 2019, but later proposals will be considered. For any questions about the organisation of a symposium please contact the conference office.


The symposium organiser(s) is/are responsible for the selection of papers to be presented. The submission date as well as the format of papers required are determined by the organisers.

The Titles, Authors and short Abstracts of all accepted presentations must be made available to the Conference Office by 31 July 2019. Note that in the case of late submissions the relevant data should be made available as soon as possible before the start of the conference.

Presentation of Papers

A session for the presentation of the papers will be reserved in the conference program by the Program Committee. A projector for the projection of slides with a notebook or mobile equipment will be available. Organisers should communicate any special wishes to the Conference Office.

Publication of Symposium Papers

Papers presented in a mini-symposium may be included in the conference proceedings. These are published after the conference. Papers will be grouped together under the title of the Mini-Symposium, allowing for an Introduction by the organiser(s). The choice of publication rests with the organiser(s) of a mini-symposium. Papers are allowed the same number of pages as all other papers included in the proceedings, i.e. 10 pages. Additional pages may be purchased by contacting the Conference Office.

The organiser(s) is/are responsible for the refereeing and acceptance of final versions of papers to be included in the proceedings. The final submission date for accepted papers to be included in the conference proceedings is 31 October 2019.

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Last updated: 2019-08-27