2021 IEEE SERVICES - IEEE International Symposium on Cloud HPC (CloudHPC)

Symposium Technical Program

DATE TIME SESSION CHAIR PRESENTATION
TUES 9/7 17:10 - 18:30 UTC
(12:10 - 13:30 CDT)


SERVICES CONGRESS PLENARY PANEL
Dennis Gannon
Indiana University
CLOUD HPC: EXPLORING THE GROWING SYNERGY BETWEEN CLOUD AND HIGH PERFORMANCE COMPUTING

Panelists:
Katherine Yelick, UC Berkeley and Lawrence Berkeley National Laboratory
Ian Foster, Argonne National Laboratory, University of Chicago
Geoffrey Fox, University of Virginia
Kate Keahey, Argonne National Laboratory, University of Chicago
TUES 9/7 18:50 - 20:10 UTC
(US CDT: 13:50 - 15:10)


CLDHPC 1
Cloud & Heterogeneous Architectures
& Opportunities for HPC
Ian Foster
Argonne National Laboratory
University of Chicago
Advancing Hybrid Cloud HPC Workflows Across State of the Art Heterogeneous Infrastructures
Steve Hebert, Nimbix Founder and CEO
The impact of the rise in cloud-based HPC
Brent Gorda, ARM Director HPC Business
HPC in a box: accelerating research with Google Cloud
Alexander Titus, Google Cloud
TUES 9/7 20:20 - 21:40 UTC
(US CDT: 15:20 - 16:40)


CLDHPC 2
HPCI in Biology & Medicine in the Cloud
Dennis Gannon
Indiana University
Computational Biology at the Exascale
Katherine Yelick, UC Berkeley and Lawrence Berkeley National Laboratory
HySec-Flow: Privacy-Preserving Genomic Computing with SGX-based Big-Data Analytics Framework
Judy Fox, Professor, University of Virginia
An automated self-service multi-cloud HPC platform applied to the simulation of cardiac valve disease with machine learning
Wolfgang Gentzsch, UberCloud, Founder & President
WED 9/8 16:30 - 17:50 UTC
(US CDT: 11:30 - 12:50)


CLDHPC 3
Using HPC to Enable AI at Scale
Dennis Gannon
Indiana University
Grand Challenges for Humanity: Cloud Scale Impact and Opportunities
Debra Goldfarb, Amazon, Director HPC Products & Strategy
Enabling AI at scale on Azure
Prabhat Ram, Microsoft, Azure HPC
Benchmarking for AI for Science in the Cloud: Challenges and Opportunities
Jeyan Thiyagalingam, STFC, UK, Head of SciML Group
WED 9/8 19:40 - 21:00 UTC
(US CDT: 14:40 - 16:00)


CLDHPC 4
Applications of Cloud Native Technology to HPC in the Cloud
Christoph Hagleitner
IBM
Serverless Supercomputing: High Performance Function as a Service
Kyle Chard, Professor, University of Chicago
Minding the Gap: Navigating the transition from traditional HPC to cloud native development
Bruce D'Amora, IBM Research
Composable Systems: An Early Application Experience
Ilkay Altintas, SDSC, Chief Data Science Officer
WED 9/8 5:40 - 7:00 UTC
(US CDT: 0:40 - 2:00)

CLOUD HPC 1
Part of the IEEE CLOUD Conference
Christoph Hagleitner
IBM
CLD_REG_123
T2FA: A Heuristic Algorithm for Deadline-constrained Workflow Scheduling in Cloud with Multicore Resource
Zaixing Sun, Chonglin Gu, Honglin Zhang and Hejiao Huang
CLD_REG_137
A Case for Function-as-a-Service with Disaggregated FPGAs
Burkhard Ringlein, Francois Abel, Dionysios Diamantopoulos, Beat Weiss, Christoph Hagleitner, Marc Reichenbach and Dietmar Fey
THU 9/9 18:10 - 19:30 UTC
(US CDT: 13:10 - 14:30)

CLDHPC 5
Distributed Computing Issues for HPC in the Cloud
Geoffrey Fox
University of Virginia
Challenges of Distributed Computing for Pandemic Spread Prediction based on Large Scale Human Interaction Data
Haiying Shen, Professor, University of Virginia
GreenDataFlow: Minimizing the Energy Footprint of Cloud/HPC Data Movement
Tevfik Kosar, Professor, University of Buffalo & NSF
IMPECCABLE: A Dream Pipeline for High-Throughput Virtual Screening, or a Pipe Dream?
Shantenu Jha, Professor, Rutgers University
THU 9/9 19:40 - 12:00
US CDT: 14:40 - 16:00)

CLDHPC 6
Cloud HPC Barriers & Opportunities
Bruce D'Amora
IBM
The Future of OpenShift
Carlos Eduardo Arango Gutierrez, Red Hat, HPC OpenShift Manager
Scientific Computing On Low-cost Transient Cloud Servers
Prateek Sharma, Indiana University
HW-accelerated HPC in the cloud: Barriers and Opportunities
Christoph Hagleitner, IBM Research
SAT 9/11 1:00 - 2:20 UTC
(US CDT 19:00 - 21:20)

CLOUD HPC 2
Part of the IEEE CLOUD Conference
Andrew Lumsdaine
University of Washington
CLD_REG_207
Usage Trends Aware VM Placement in Academic Research Computing Clouds
Mohamed Elsakhawy and Michael Bauer
CLD_REG_210
Neon: Low-Latency Streaming Pipelines for HPC
Pierre Matri and Robert Ross

Call for Papers

Cloud computing is traditionally defined in terms of data and compute services that support on-demand applications that scale to thousands of simultaneous users. High Performance Computing (HPC) is associated with massive supercomputers that run highly parallel programs for small groups of users. However, over the last five years, the demands of the scientific and engineering research community have created an evolutionary pressure to merge the best innovations of these two models. HPC centers have started to use cloud-native technologies like data object stores and cloud tools and processes to develop and deploy software. On the other side, cloud data centers are integrating advanced accelerators on each node and deploy high-performance interconnects with latency optimizations known from HPC. Furthermore, the AI revolution that was initially nurtured by the public cloud companies with their hyperscale datacenters, is increasingly finding adoption in the scientific and engineering applications on supercomputers.

The IEEE CloudHPC Symposium will explore all aspects of the growing synergy between Cloud computing and HPC. Topics of special interest include the following:

  • HPC workflows using hybrid cloud and supercomputer configurations
  • Innovative tools and usage for (Cloud) HPC application developers
  • Scalability, performance optimization and benchmarking in Cloud HPC
  • Next generation interactive operating environments for hybrid cloud deployments combining on-prem and cloud infrastructure
  • The evolution and deployment of advanced accelerators (GPUs, FPGAs, TPUs, etc.) in Cloud HPC
  • The role of cloud-native infrastructure (including containers, Kubernetes and notebooks) to solve significant scientific and engineering problems
  • The future of MPI in Cloud HPC
  • An exploration of the role Cloud HPC played in the pandemic response
  • Using advanced AI methods in the cloud for improving science and business outcomes
  • Industry design, engineering, and/or automation enabled by advanced Cloud HPC technologies
  • The unique security challenges in Cloud HPC

The inaugural IEEE CloudHPC Symposium provides a forum for leading researchers, practitioners, and visionaries to share their R&D findings, experiences, and/or visions of Cloud HPC. It will be held as a cross-conference event at IEEE SERVICES 2021, featuring distinguished speeches, panels, invited talks/presentations, and joint research paper presentations with IEEE CLOUD 2021. Please stay tuned for program updates. We extend an invitation to all to participate and make it a success.

MANUSCRIPT GUIDELINES AND SUBMISSION INFORMATION

Please download the paper template in WORD, LaTeX or Overleaf.
Language: English
Paper size and format: US Letter; Two-column format in the IEEE style
Page limit: * Every full paper submission can include up to 10 pages for the main contents (including all text, footnotes, figures, tables and appendices) with additional pages for appropriate references.
* Up to three pages for panel position statement submission (including main contents and references).

SUBMISSION LINK

Please submit your papers to the Symposium via EasyChair at https://easychair.org/conferences/?conf=ieeeservices2021

PUBLICATION

All submissions will be reviewed by the Program Committee. Accepted papers of the Symposium will be included in the Congress proceedings for IEEE CLOUD 2021 and published in IEEE Xplore.

IMPORTANT DATES (at 5:00 AM UTC)

Paper submission due: 20 June 2021
Notification to authors: 5 July 2021
Camera-ready and registration due: 15 July 2021

Organization

Honorary General Chairs
Ian Foster, University of Chicago/ANL
Geoffrey C. Fox, Indiana University

General Chairs
Dennis Gannon, Indiana University
James Sexton, IBM Research, TJ Watson Research Center

Program Chairs
Christoph Hagleitner, IBM Research, TJ Watson Research Center
Andrew Lumsdaine, University of Washington