6th Workshop on Scientific Cloud Computing (ScienceCloud) 2015

Workshop to be held with ACM HPDC

Room D129-130

June 16 2015, Portland, OR, USA


Download CFP (.txt) or Flier (.pdf).

News

Schedule (Rrom D129-130)

9:00 - 9:15 Workshop Introduction
9:15 - 10:00 Keynote: Challenges of Running Scientific Workflows in Cloud Environments
Ewa Deelman, Information Sciences Institute, University of Southern California

Abstract: This talk will touch upon the challenges of running scientific workflows in distributed environments such as academic and commercial clouds. It will describe the Pegasus Workflow Management System and how it manages the execution of a variety of scientific workflows. Pegasus is a system that maps high-level workflow descriptions onto the available, potentially distributed compute and data resources. It supports workflow re-usability by making the same workflow description portable across infrastructures, including different clouds. A single workflow can run on a particular cloud or across heterogeneous clouds. Pegasus also optimizes the workflow from the point of view of performance and reliability. The talk will explore the options for data management, the impact of file system choice on performance, and general issues of resource provisioning. It will examine the interplay between resource provisioning and workflow execution, and how knowledge about the workflow structure and task characteristics can be used to make better resource provisioning decisions at runtime. The talk will describe the concept of a Shadow Queue and how it is used to predict future workflow needs. This information is then made available to a provisioning system such as ORCA to provision compute and network resources as needed while the workflow is executing.
10:00- 10:30 Scaling VM Deployment in an Open Source Cloud Stack
Kaveh Razavi, Stefania Costache, Andrea Gardiman, Kees Verstoep, and Thilo Kielmann
10:30 - 11:00 Architecting a Persistent and Reliable Configuration Management System
Dmitry Duplyakin, Matthew Haney, and Henry Tufo
11:00 - 11:20 Break
11:20 - 12:30 FCRC Plenary
12:30 - 14:00 Lunch
14:00 - 14:30 On Performance Resilient Scheduling for Scientific Workflows in HPC Systems with Constrained Storage Resources
Yang Wang, Wei Shi and Eduardo Berrocal (presented by Ke Wang)
14:30 - 15:30 Panel: Real-time scientific data stream processing
Barney Maccabe, Ioan Raicu, Doug Thain, Rui Zhang
15:30 - 16:00 Break
16:00 - 16:20 High-Performance Storage Support for Scientific Applications on the Cloud
Dongfang Zhao, Xu Yang, Iman Sadooghi, Gabriele Garzoglio, Steven Timm, and Ioan Raicu
16:20 - 16:40 Achieving Performance Isolation on Multi-Tenant Networked Clouds Using Advanced Block Storage Mechanisms
Paul Ruth; Anirban Mandal; Claris Castillo; Robert Fowler; Jeff Tilson; Ilya Baldin; Yufeng Xin
16:40 - 17:00 A Dynamically Scalable Cloud Data Infrastructure for Sensor Networks
Tonglin Li, Kate Keahey, Ke Wang, Dongfang Zhao, and Ioan Raicu
17:00 - 17:15 Conference closing

Important dates

Overview

Computational and Data-Driven Sciences have become the third and fourth pillar of scientific discovery in addition to experimental and theoretical sciences. Scientific Computing has already begun to change how science is done, enabling scientific breakthroughs through new kinds of experiments that would have been impossible only a decade ago. Today.s .Big Data. science is generating datasets that are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. The support for data intensive computing is critical to advance modern science as storage systems have exposed a widening gap between their capacity and their bandwidth by more than 10-fold over the last decade. There is a growing need for advanced techniques to manipulate, visualize and interpret large datasets. Scientific Computing is the key to solving .grand challenges. in many domains and providing breakthroughs in new knowledge, and it comes in many shapes and forms: high-performance computing (HPC) which is heavily focused on compute-intensive applications; high-throughput computing (HTC) which focuses on using many computing resources over long periods of time to accomplish its computational tasks; many-task computing (MTC) which aims to bridge the gap between HPC and HTC by focusing on using many resources over short periods of time; and data-intensive computing which is heavily focused on data distribution, data-parallel execution, and harnessing data locality by scheduling of computations close to the data.

The 6th workshop on Scientific Cloud Computing (ScienceCloud) will provide the scientific community a dedicated forum for discussing new research, development, and deployment efforts in running these kinds of 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. The workshop will aim to address questions such as: What architectural changes to the current cloud frameworks (hardware, operating systems, networking and/or programming models) are needed to support science? Dynamic information derived from remote instruments and coupled simulation, and sensor ensembles that stream data for real-time analysis are important emerging techniques in scientific and cyber-physical engineering systems. How can cloud technologies enable and adapt to these new scientific approaches dealing with dynamism? How are scientists using clouds? Are there scientific HPC/HTC/MTC workloads that are suitable candidates to take advantage of emerging cloud computing resources with high efficiency? Commercial public clouds provide easy access to cloud infrastructure for scientists. What are the gaps in commercial cloud offerings and how can they be adapted for running existing and novel eScience applications? What benefits exist by adopting the cloud model, over clusters, grids, or supercomputers? What factors are limiting clouds use or would make them more usable/efficient?

This workshop encourages interaction and cross-pollination between those developing applications, algorithms, software, hardware and networking, emphasizing scientific computing for such cloud platforms. We believe the workshop will be an excellent place to help the community define the current state, determine future goals, and define architectures and services for future science clouds.

Topics of interest

We invite the submission of original work that is related to the topics below. The papers can be either short (4 pages) position papers, or long (8 pages) research papers. Topics of interest include (in the context of Cloud Computing):

Submission instructions

Authors are invited to submit papers with unpublished, original work of not more than 8 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages (including all text, figures, and references), as per ACM 8.5 x 11 manuscript guidelines (document templates can be found at http://www.acm.org/sigs/publications/proceedings-templates). 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 the above guidelines can be submitted through the workshop's paper submission system: https://easychair.org/conferences/?conf=sciencecloud2015.

Organizers

Steering Committee

Programme Committee