[hpc-announce] CALL FOR PAPERS Special Issue - Future Generations Computer Systems: Approximate Computing: the need for efficient and sustainable computing

[Wisser, Grace]

CALL FOR PAPER Future Generation Computer Systems Special Issue
Approximate Computing: the need for efficient and sustainable computing
https://urldefense.us/v3/__https://www.sciencedirect.com/special-issue/314705/approximate-computing-the-need-for-efficient-and-sustainable-computing__;!!G_uCfscf7eWS!eWVpiR3EMKiZOMig6wMXxIFnjfds7iBBpOi_C4LOZsGBthrtGcN-kx06vjgiD9K4IVVOHpKp6KQSTZyC0hPq4No$ 
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MOTIVATION AND SCOPE

Today, computing systems face unprecedented computational demands. They serve as bridges between the digital and physical world, processing vast data from diverse sources. Our digital world is constantly producing an immense volume of data. According to recent estimates, millions of terabytes of data are created each day. To handle this immense volume of data, increasingly sophisticated and resource-constrained devices are deployed at the edge, where energy and power efficiency takes center stage. Additionally, the growth of modern AI models, particularly neural networks, has led to boundless computational and power demands. For example, GPT-3 featuring 175 billion parameters, BERT large equipped with 340 million parameters, require high energy costs for training and inferencing data. Approximate Computing (AxC) provides a promising solution: by intentionally allowing slight inaccuracies in computations, AxC significantly reduces overhead (including energy, area, and latency) while preserving practical accuracy levels. These paradigms find applications across several domains. With the intent of navigating the intricate balance between accuracy, reliability, and energy efficiency, exploring Approximate Computing (AxC) techniques becomes crucial.

The proposed Special Issue (SI) investigates the intersection of energy-efficient computing and accuracy of state-of-the-art workloads, shedding light on innovative approaches and practical implementations.

The potential areas of interest for the proposed SI include, but are not limited to, the following topics:

*Approximation for Deep Learning applications, including Large Language Models (LLMs)
*Approximation techniques for emerging processor and memory technologies
*Approximation-induced error modeling and propagation
*Approximation in edge computing applications
*Approximation in HPC and embedded systems
*Approximation in Foundation Models
*Approximation in reconfigurable computing
*Architectural support for approximation
*Cross-layer approximate computing
*Hardware/software co-design of approximate systems
*Dependability of approximate circuits and systems
*Design automation of approximate architectures
*Design of approximate reconfigurable architectures
*Error resilient Near-Threshold Computing
*Methods for monitoring and controlling approximation quality
*Modeling, specification, and verification of approximate circuits, and systems
*Safety and reliability applications of approximate computing
*Security in the context of approximation
*Software-based fault-tolerant technique for approximate computing
*Test and fault tolerance of approximate systems

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GUEST EDITORS

Annachiara Ruospo
Politecnico di Torino, Italy
annachiara.ruospo at polito.it

Salvatore Barone
University of Naples Federico II, Italy
salvatore.barone at unina.it

Jorge Castro-Godinez
School of Electronics Engineering
Instituto Tecnologico de Costa Rica, Costa Rica
jocastro at itcr.ac.cr

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IMPORTANT DATES


Deadline for paper submission: January 31, 2025

Latest acceptance deadline for all papers: May 21, 2025

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MANUSCRIPT SUBMISSION INSTRUCTIONS

The format of submitted manuscripts that must match the format of regular papers in Future Generation Computer Systems Journal. All submissions deemed suitable by the editors to be sent for peer review will be reviewed by at least three independent reviewers. Reviewers will have to submit their recommendation letter within 1 month. If this deadline is missed, the manuscript will be assigned to a new reviewer. Once your manuscript is accepted, it will go into production to be published in the special issue.

The FGCS’s submission system (Editorial Manager®) will be open for submissions to our Special Issue from November 1st, 2024. When submitting your manuscript please select the article type VSI: Approximate Computing (AxC).

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MANUSCRIPT FORMATTING GUIDELINES

GUIDE FOR AUTHORS: https://urldefense.us/v3/__https://www.elsevier.com/journals/future-generation-computer-systems/0167-739X/guide-for-authors__;!!G_uCfscf7eWS!eWVpiR3EMKiZOMig6wMXxIFnjfds7iBBpOi_C4LOZsGBthrtGcN-kx06vjgiD9K4IVVOHpKp6KQSTZyCC83frHE$ 

* Please use Elsevier's Latex Style with "5p, times" option. So your document should start with \documentclass[5p,times]{elsarticle}
* You are recommended to use the Elsevier article class elsarticle.cls (https://urldefense.us/v3/__https://ctan.org/tex-archive/macros/latex/contrib/elsarticle__;!!G_uCfscf7eWS!eWVpiR3EMKiZOMig6wMXxIFnjfds7iBBpOi_C4LOZsGBthrtGcN-kx06vjgiD9K4IVVOHpKp6KQSTZyCiG2-OF4$ ) to prepare your manuscript and BibTeX (https://urldefense.us/v3/__http://www.bibtex.org/__;!!G_uCfscf7eWS!eWVpiR3EMKiZOMig6wMXxIFnjfds7iBBpOi_C4LOZsGBthrtGcN-kx06vjgiD9K4IVVOHpKp6KQSTZyCuixr1YI$ ) to generate your bibliography.
* Our LaTeX  (https://urldefense.us/v3/__https://www.elsevier.com/latex__;!!G_uCfscf7eWS!eWVpiR3EMKiZOMig6wMXxIFnjfds7iBBpOi_C4LOZsGBthrtGcN-kx06vjgiD9K4IVVOHpKp6KQSTZyC8z7GlRU$ ) site has detailed submission instructions, templates and other information.
* Article submitted to FGCS should be strictly double column, single spaced and limited to 18 pages; including all figures, tables, references.
* A manuscript longer than 18 pages will not be considered for review and returned to author to be revised to the correct format.

To view a complete list of the Call for Papers for Future Generation Computer Systems Journal, visit: https://urldefense.us/v3/__https://www.sciencedirect.com/journal/future-generation-computer-systems/about/call-for-papers__;!!G_uCfscf7eWS!eWVpiR3EMKiZOMig6wMXxIFnjfds7iBBpOi_C4LOZsGBthrtGcN-kx06vjgiD9K4IVVOHpKp6KQSTZyCGwjijVk$