[hpc-announce] 4th IEEE International Workshop on RESource DISaggregation in High Performance Computing (RESDIS’24)

[CHRISTIAN PINTO]

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                             CALL FOR PAPERS
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4th IEEE International Workshop on RESource DISaggregation in High
Performance Computing (RESDIS?24)

To be held in conjunction with The International Conference for High
Performance Computing, Networking, Storage and Analysis (SC?24)

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                        https://urldefense.us/v3/__https://resdis.github.io/__;!!G_uCfscf7eWS!YkiCDiYqwJ5d767L17B82ksHGgzbYnjdzSf-fGSlso_aGT4LCKK1W_KRcdo_WwHf4jyZKCQdwSA_WgK4mOZQLTZINkIZQO8$ 
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Disaggregation is an emerging compute paradigm that splits existing monolithic
servers into a number of consolidated single-resource pools that communicate
over a fast interconnect. This model decouples individual hardware resources,
including tightly coupled ones such as processors and memory, and enables the
composition of logical compute platforms with flexible and dynamic hardware
configurations.

The concept of disaggregation is driven by various recent trends in
computation. From an application perspective, the increasing importance of
data analytics and machine learning workloads in HPC centers brings
unprecedented need for memory capacity, which is in stark contrast with the
growing imbalance in the peak compute-to-memory capacity ratio of traditional
system board based server platforms where memory modules are co-located with
processors.  Meanwhile, traditional simulation workloads leave memory
underutilized. At the hardware front, the proliferation of heterogeneous,
special purpose computing elements promotes the need for configurable compute
platforms, while at the same time, the increasing maturity of optical
interconnects raises the prospects of better distance independence in
networking infrastructure.

The workshop intends to explore various aspects of resource disgregation,
composability and their implications for high performance computing, both in
dedicated HPC centers as well as in cloud environments.


TOPICS OF INTEREST:
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- Disaggregated hardware in high-performance computing
- Operating systems and runtime support for disaggregated platforms
- Simulation of disaggregated platforms with existing infrastructure
- Runtime systems and programming abstractions for disaggregation and
  composability
- Networking for disaggregation, including silicon photonics and optical
  interconnects
- Implications of resource disaggregation for scientific computing and
  HPC applications
- Algorithm design for disaggregated and composable systems
- Disaggregated high throughput storage
- Disaggregated heterogeneous accelerators (GPUs, FPGAs, AI Accelerators, etc.)
- Resource management in disaggregated and composable platforms


TIMELINE AND SUBMISSION PROCEDURE:
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Submission deadline:               August 9, 2024 (AoE)
Author notification:               September 6, 2024
Final papers deadline:             September 27, 2024
Workshop date:                     November 17, 2024

The workshop proceedings will be published electronically via the
IEEE Computer Society Digital Library.  Submitted manuscripts must
use the proceedings templates at:

https://urldefense.us/v3/__https://www.ieee.org/conferences/publishing/templates.html__;!!G_uCfscf7eWS!YkiCDiYqwJ5d767L17B82ksHGgzbYnjdzSf-fGSlso_aGT4LCKK1W_KRcdo_WwHf4jyZKCQdwSA_WgK4mOZQLTZIE4-ni50$ 

Submissions must be between 5 and 8 pages, including references and figures.
Prospective authors should submit their papers in PDF format through
Linklings? submission site:

https://urldefense.us/v3/__https://submissions.supercomputing.org/?page=Submit&id=SCWorkshopRESDISSubmission&site=sc24__;!!G_uCfscf7eWS!YkiCDiYqwJ5d767L17B82ksHGgzbYnjdzSf-fGSlso_aGT4LCKK1W_KRcdo_WwHf4jyZKCQdwSA_WgK4mOZQLTZIlBr4LaM$ 


WORKSHOP CHAIRS:
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Balazs Gerofi           Intel Corporation, USA
John Shalf              Lawrence Berkeley National Laboratory, USA
Christian Pinto         IBM Research Europe, Ireland


PROGRAM COMMITTEE:
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Michael Aguilar           Sandia National Laboratories, USA
Larry Dennison            Nvidia, USA
Thaleia Dimitra Doudali   IMDEA Software Institute, Spain
Kyle Hale                 Illinois Institute of Technology, USA
John (Jack) Lange         Oak Ridge National Laboratory, USA
Ivy Peng                  KTH Royal Institute of Technology, Sweden
Yu Tanaka                 Fujitsu, Japan
Ga?l Thomas               T?l?com SudParis, France