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ABEL SOUZA

Research Associate, Manning College of Information and Computer Sciences.

College of Information and Computer Sciences

140 Governors Dr.

RM A313 (LGRC)

Amherst, MA 01003

Hello and welcome! I am Abel Souza, a Postdoctoral Researcher in the College of
Information & Computer Sciences at the University of Massachusetts Amherst. I
work with Prof. Prashant Shenoy in the Laboratory for Advanced System Software.

Prior to joining UMass, I was a PhD student in the Department of Computing
Science at Umeå University (Sweden). I worked in the Autonomous Distributed
Systems Lab. under the guidance of Dr. Johan Tordsson and Prof. Erik Elmroth.
The topic of my research was Data Analytics for Resource Management in High
Performance (HPC) and Cloud datacenters.

Today, my research predominantly focuses on distributed and data-intensive
systems that support AI, Machine Learning, and web workloads. Recently, my work
has extended to address sustainable and efficient approaches for designing,
architecting, and managing both cloud and edge platforms with the aim of
achieving zero-carbon emissions. A key theme in my research explores the
efficient application of predictive analytics methods to process and model vast
amounts of data, tailoring resource management holistically to applications.
This involves determining the optimal quantity and type of resources to
allocate, as well as the most effective deployment times and locations.

NEWS

Mar 21, 2024 Applications to the 2024 UMass Amherst Turing Summer Program open!
Mar 12, 2024 Paper On the Implications of Choosing Average versus Marginal
Carbon Intensity Signals on Carbon-aware Optimizations accepted! Feb 12, 2024
Paper SLO-Power accepted! Feb 7, 2024 Paper On the Limitations of Carbon-Aware
Temporal and Spatial Workload Shifting in the Cloud accepted! Nov 23, 2023 A new
website is launched!

SELECTED PUBLICATIONS

1. EuroSys
On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in
the Cloud
Thanathorn Sukprasert, Abel Souza, Noman Bashir, David Irwin, and Prashant
Shenoy
In Proceedings of the 19th European Conference on Computer Systems
(EuroSys), 2024

Abs arXiv Bib

Cloud platforms have been focusing on reducing their carbon emissions by
shifting workloads across time and locations to when and where low-carbon
energy is available. Despite the prominence of this idea, prior work has
only quantified the potential of spatiotemporal workload shifting in narrow
settings, i.e., for specific workloads in select regions. In particular,
there has been limited work on quantifying an upper bound on the ideal and
practical benefits of carbon-aware spatiotemporal workload shifting for a
wide range of cloud workloads. To address the problem, we conduct a detailed
data-driven analysis to understand the benefits and limitations of
carbon-aware spatiotemporal scheduling for cloud workloads. We utilize
carbon intensity data from 123 regions, encompassing most major cloud sites,
to analyze two broad classes of workloads – batch and interactive – and
their various characteristics, e.g., job duration, deadlines, and SLOs. Our
findings show that while spatiotemporal workload shifting can reduce
workloads’ carbon emissions, the practical upper bounds of these carbon
reductions are currently limited and far from ideal. We also show that
simple scheduling policies often yield most of these reductions, with more
sophisticated techniques yielding little additional benefit. Notably, we
also find that the benefit of carbon-aware workload scheduling relative to
carbon-agnostic scheduling will decrease as the energy supply becomes
“greener”.

@inproceedings{sukprasert2024limitations,
title = {On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in the Cloud},
author = {Sukprasert, Thanathorn and Souza, Abel and Bashir, Noman and Irwin, David and Shenoy, Prashant},
year = {2024},
booktitle = {Proceedings of the 19th European Conference on Computer Systems (EuroSys)},
}

2. SoCC
Enabling sustainable clouds: The case for virtualizing the energy system
Noman Bashir, Tian Guo, Mohammad Hajiesmaili, David Irwin, Prashant
Shenoy, Ramesh Sitaraman, Abel Souza, and Adam Wierman
In Proceedings of the ACM Symposium on Cloud Computing, 2021

Bib HTML PDF Video

@inproceedings{bashir2021enabling,
presentation = {https://youtu.be/m0RLpmOCpv4?si=en2plapYoPNcP_-5},
title = {Enabling sustainable clouds: The case for virtualizing the energy system},
author = {Bashir, Noman and Guo, Tian and Hajiesmaili, Mohammad and Irwin, David and Shenoy, Prashant and Sitaraman, Ramesh and Souza, Abel and Wierman, Adam},
booktitle = {Proceedings of the ACM Symposium on Cloud Computing},
pages = {350--358},
year = {2021},
}

3. ASPLOS
Ecovisor: A virtual energy system for carbon-efficient applications
Abel Souza, Noman Bashir, Jorge Murillo, Walid Hanafy, Qianlin Liang, David
Irwin, and Prashant Shenoy
In Proceedings of the 28th ACM International Conference on Architectural
Support for Programming Languages and Operating Systems, Volume 2, 2023

arXiv Bib HTML PDF Code Slides

@inproceedings{ecovisor,
title = {Ecovisor: A virtual energy system for carbon-efficient applications},
author = {Souza, Abel and Bashir, Noman and Murillo, Jorge and Hanafy, Walid and Liang, Qianlin and Irwin, David and Shenoy, Prashant},
booktitle = {Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2},
pages = {252--265},
year = {2023},
doi = {10.1145/3575693.3575709},
}

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