[hpc-announce] Call For Papers - Active'17: First International Workshop on Data Management on Virtualized Active Systems (In Conjunction with IEEE ICDE 2017)

[Kaiwen Zhang]

CALL FOR PAPERS



Active'17: First International Workshop on Data Management on Virtualized
Active Systems (In Conjunction with IEEE ICDE 2017). San Diego, CA, USA.
April 22, 2017



https://active-conf.github.io/





OBJECTIVES:

The objective of this one-day workshop is to bring researchers and
practitioners together in order to investigate opportunities in exploiting
virtualized active (compute-enabled) technologies such as active memory,
active network, and active storage for accelerating data-intensive
workloads. Furthermore, this workshop aims at investigating issues in
realizing active capabilities (enabled by hardware accelerators such as
SSDs, GPUs, FPGAs, and ASICs) in the entire system stack running on cloud.
The workshop aims at providing a forum for academia and industry to
exchange ideas through research and position papers.





SCOPE:

The recent popularity of Big Data applications has renewed interest in
developing and optimizing data-intensive workloads. In addition to the
traditional scientific computing domain, Big Data phenomena are observed in
a variety of new domains such as Internet of Things (IoT), social analytic,
personalized health and precision medicine, bioinformatics, energy
informatics, and emergency response and disaster management. The Big Data
workloads are characterized by unprecedented volumes and velocity of data,
both historic and transient, very high-speed data flows (e.g., from sensor
networks), and diverse variety of data from completely unstructured text
documents, to structured relational tables or matrices, to photos and
videos. Analyzing vast quantities of such complex data (partially powered
by machine learning) is becoming as important as the traditional
massive-scale data management.



Unfortunately, existing approaches to solve data-intensive problems are
woefully inadequate to address the challenges raised by the Big Data
applications. Specifically, these approaches require data to be processed
to be moved near the computing resources. These data movement costs can be
prohibitive for large data sets such as those observed in the
aforementioned workloads. One way to address this problem is to bring
virtualized computing resources closer to data, whether it is at rest or in
motion. The premise of "active" systems is a new holistic view of the
system in which every data medium (whether volatile or non-volatile) and
every communication channel becomes compute-enabled.



Although prototypes of systems with active technologies are currently
available, there is a very limited exploitation of their capabilities in
real-life problems. The proposed workshop aims to evaluate different
aspects of the active systems stack and understand the impact of active
technologies (including but not limited to hardware accelerators such as
SSDs, GPUs, FPGAs, and ASICs) on different applications workloads.
Specifically, the workshop aims to understand the role of modern hardware
to enable active medium (whether network, storage, or memory) over the
entire path and the lifecycle of data, especially as today's database
system opt for hierarchies of storage and memory. Furthermore, we aim to
revisit the interplay between algorithmic modeling, compiler and
programming languages, virtualized runtime systems and environments, and
hardware implementations, for effective exploitation of active technologies.





TOPICS COVERED INCLUDE, BUT ARE NOT LIMITED TO:

1) Data Management Issues in Active Systems (e.g., active network, storage,
and memory)

2) Data Management Issues in Software-Hardware-System Co-design

3) Active Technologies (e.g., SSDs, GPUs, FPGAs, and ASICs) in Co-design
Architectures

4) Query Orchestration and Execution Models in Co-design Architectures

5) Enabling Partial Computation or Best Effort Computation in Co-design
Architectures

6) Offloading Computation to Accelerators in Co-processor Design

7) Placing Accelerator on the Data Path in Co-placement Design

8) Programming Methodologies for Data-intensive Workloads on Active
Technologies

9) Virtualizing Active Technologies on Cloud (e.g., Scalability and
Security)

10) Exploiting Active Technologies in Modern Databases (e.g., NoSQL and
NewSQL)

11) Extending Runtime of Big Data Systems (e.g., Spark, Hadoop) with Active
Technologies

12) Autonomic Tuning for Data Management Workloads in Co-design
Architectures

13) Algorithms and Performance Models for Active Memory and Storage
Sub-systems

14) Novel Applications of Low-Power Modern Processors, GPUs, FPGAs, and
ASICs

15) Novel Applications of Transactional Memory in Co-design Architectures

16) Workload-aware System Co-design for Emerging Applications (e.g.,
Internet-of-Things, Personalized Health, and Precision Medicine)





Submission Dates:

Paper submissions:       December 10, 2016

Notification to authors: January 10, 2017

Camera-ready copy due:   January 24, 2017

Workshops:               April 22, 2017






WORKSHOP CO-CHAIRS:

Rajesh R. Bordawekar (IBM T.J. Watson Research Center)

Mohammad Sadoghi (Purdue University)



PUBLICITY CHAIR:

Kaiwen Zhang (Technical University of Munich)



PROGRAM COMMITTEE:

Nipun Agarwal (Oracle)

Spyros Blanas (Ohio State University)

Khuzaima Daudjee (University of Waterloo)

Peter M. Fischer (University of Freiburg)

Blake G. Fitch (IBM Research, Zurich)

Boris Glavic (Illinois Institute of Technology)

Hans-Arno Jacobsen (Middleware Systems Research Group)

Kajan Kanagaratnam (IBM, Toronto)

Tirthankar Lahiri (Oracle)

Mohammadreza Najafi (Technical University of Munich)

Ilia Petrov (TU Darmstadt)

Tilmann Rabl (TU Berlin)

Tiark Rompf (Purdue University)

Mohamed Sarwat (Arizona State University)

Divesh Srivastava (AT&T Labs Research)

Dina Thomas (Pure Storage)

Stratis Viglas (University of Edinburgh)






STRUCTURE:

Active 2017 will be organized along two tracks:



1) Regular Research Papers: These papers should report original research
results or significant case studies. They should be at most 8 pages.



2) Position Papers: These papers should report novel research directions or
identify challenging problems. They should be at most 4 pages.



All submissions must be prepared according to the ICDE formatting
guidelines.






PROCEEDINGS:

All accepted papers will be published in the ICDE proceedings and will also
become publicly available through the IEEE Xplore.



SUBMISSION INFORMATION:

Papers have to be submitted electronically as PDF files via EasyChair:

https://easychair.org/conferences/?conf=active17
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