10th Workshop on Scientific Cloud Computing
This year, ScienceCloud is organized jointly with the 1st Workshop on Converged Computing Infrastructure. We have set up an exciting program with a keynote by Ian Foster and a discussion panel.
9:00-9:10 Opening and Keynote Introduction
9:10-10:20 Keynote by Ian Foster (Argonne National Laboratory): Coding the Continuum
10:20-10:30 ElasticPipe: An Efficient and Dynamic Model-Parallel Solution to DNN Training. Presenter: Jinkun Geng (Tsinghua University)
10:30-10:50 Towards a Smart, Internet-Scale Cache Service for Data Intensive Scientific Applications. Presenter: Yubo Qin (Rutgers University)
10:50-11:20 Coffee Break
11:20-12:30 FCRC Plenary Session
This session takes place at Symphony Hall (Immediately south of Convention Center)
This talk on differential privacy and the US Census will be given by Cynthia Dwork.
12:30-14:00 Lunch Break
14:00-15:00 Panel: Infrastructure: what scientists need from HPC, Clouds, and Big Data/ML systems. Panelists: Alexandru Iosup (TU Delft), Jay Lofstead (Sandia National Laboratories), Aparna Chandramowlishwaran (University of California, Irvine)
15:00-15:20 Deconstructing the 2017 Changes to AWS Spot Market Pricing. Presenter: Matt Baughman (Minerva Schools at KGI)
15:20-15:40 Horizontal or Vertical? A Hybrid Approach to Large-Scale Distributed Machine Learning. Presenter: Jinkun Geng (Tsinghua University)
15:40-15:45 Closing Remarks
"Infrastructure: what scientists need from HPC, Clouds, and Big Data/ML systems"
This panel will bring together three scientists with diverse backgrounds and research interests and will gather their perspectives on the past, present, and future trends in computing infrastructure. HPC, Clouds, and systems for Big Data and Machine Learning are within the scope of the panel. The convergence of the technologies coming from different fields is a topic of particular importance in this discussion. The organizers expect to see an engaging, open and informal discussion with active participation from the audience.
Coding the Continuum
In 2001, as early high-speed networks were deployed, George Gilder observed that “when the network is as fast as the computer's internal links, the machine disintegrates across the net into a set of special purpose appliances.” Two decades later, our networks are 1,000 times faster, our appliances are increasingly specialized, and our computer systems are indeed disintegrating. As hardware acceleration overcomes speed-of-light delays, time and space merge into a computing continuum. Familiar questions like “where should I compute,” “for what workloads should I design computers,” and "where should I place my computers” seem to allow for a myriad of new answers that are exhilarating but also daunting. Are there concepts that can help guide us as we design applications and computer systems in a world that is untethered from familiar landmarks like center, cloud, edge? I propose some ideas and report on experiments in coding the continuum.
The 10th workshop on Scientific Cloud Computing (ScienceCloud) will provide the scientific community a dedicated forum for discussing new research, development, and deployment efforts in running scientific computing workloads on Cloud Computing infrastructures. The ScienceCloud workshop will focus on the use of cloud-based technologies to meet new compute-intensive and data-intensive scientific challenges that are not well served by the current supercomputers, grids, and HPC clusters. This workshop will encourage interaction and cross-pollination between those developing applications, algorithms, software, hardware and networking, emphasizing scientific computing for cloud platforms. The workshop will be an excellent place to help the community define the current state, determine future goals, and discuss promising technologies and techniques.
- Scientific application cases studies on cloud infrastructures
- Performance evaluation of Cloud environments and technologies
- Fault tolerance and reliability in cloud systems
- Data-intensive workloads and tools in clouds
- Use of programming models (e.g. Spark, Map-Reduce) and their implementations in cloud settings
- Storage cloud architectures in cloud settings
- I/O and Big Data management in the cloud
- Workflow and resource management in the cloud
- Use of cloud technologies (e.g., NoSQL databases) for scientific applications
- Data streaming and dynamic applications in the cloud
- Heterogeneous resources (network, storage, compute) and edge/fog infrastructure
- Many-Task Computing in the cloud
- Application of cloud concepts in HPC environments or vice versa
- High performance parallel file systems in virtual environments
- Virtualized high performance I/O network interconnects
- Virtualization, containers, and dynamic provisioning
- Distributed Operating Systems in cloud settings
- Many-core computing and accelerators (e.g. GPUs, MIC) in the cloud
- Analysis of management complexity, cost, variability, and reproducibility of cloud and IoT environments
- Stream processing in the cloud
- Stream data management for scientific applications in the cloud
- Edge, Fog and hybrid Cloud - Edge / Fog computing
Paper submission deadline: April 9, 2019 AoE (Extended; original: April 2, 2019)
Paper notification due: May 1, 2019
Camera ready papers: May 9, 2019
Workshop: June 25, 2019
Authors are invited to submit:
- Full 8-page papers
- Short/work-in-progress 4-page papers
Authors are invited to submit papers describing unpublished, original research. All submitted manuscripts should be formatted using the ACM Master Template with sigconf format (please be sure to use the current version). All necessary documentation can be found at: https://www.acm.org/publications/proceedings-template. The maximum lengths are 8 and 4 pages (including all text, figures, and references). All papers must be in English. We use single-blind reviewing process, so please keep the authors names, publications, etc., in the text.
Papers will be peer-reviewed, and accepted papers will be published in the workshop proceedings as part of the ACM Digital Library.
Papers conforming to these guidelines should be submitted through EasyChair: https://easychair.org/conferences/?conf=sciencecloud2019
Roy Campbell, University of Illinois at Urbana-Champaign
Aparna Chandramowlishwaran, University of California, Irvine
Kyle Chard, University of Chicago and Argonne National Laboratory
Ryan Chard, Argonne National Laboratory
Yong Chen, Texas Tech University
Eric Eide, University of Utah
Daniel S. Katz, University of Illinois Urbana-Champaign
Anthony Kougkas, Illinois Institute of Technology
Pierre Matri, Argonne National Laboratory
Radu Prodan, University of Klagenfurt
Michael Sevilla, TidalScale, Inc.
Pedro Paulo Silva, INRIA - LIP
Austin Todd, National Renewable Energy Laboratory
Alexandru Uta, Vrije Universiteit Amsterdam
Teng Wang, Florida State University
Dongfang Zhao, University of Nevada, Reno