Parallel Computing Systems

Research group

The Parallel Computing Systems (PCS) group at the University of Amsterdam performs research on the design, programming and run-time management of multi-core and multi-processor computer systems. The modeling, analysis and optimization of the extra-functional aspects of these systems, such as performance, power/energy consumption, reliability but also the degree of productivity to design and program these systems, play a pivotal role in this work.

News

The paper 'Cache Interference-aware Task Partitioning for Non-preemptive Real-time Multi-core Systems' was accepted for ACM Transactions on Embedded Computing Systems.

Sep 20, 2021

The paper 'Model-Driven System-Performance Engineering for Cyber-Physical Systems' was accepted for the Industry Session at IEEE/ACM ESWeek 2021.

Sep 17, 2021

The paper 'T-TSP: Transient-Temperature Based Safe Power Budgeting in Multi-/Many-Core Processors' was accepted for IEEE ICCD 2021.

Sep 17, 2021

The paper 'Exploring Cell-based Neural Architectures for Embedded Systems' was accepted at the ITEM'21 workshop

Aug 24, 2021

Science & Design project 'Towards Zero-Waste Computing: Energy Labels for Digital Services' granted!

Aug 24, 2021
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Meet the Team

Group Chair

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Andy D. Pimentel

Full Professor

Staff

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Ana Lucia Varbanescu

Associate Professor

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Clemens Grelck

Associate Professor

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Anuj Pathania

Assistant Professor

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Benny Akesson

Professor by special appointment

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Simon Polstra

Scientific Programmer / Lecturer

Postdoctoral Researchers

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Sobhan Niknam

Postdoctoral Researcher

PhD students

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Yixian Shen

Phd Student

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Ehsan Aghapour

Phd Student

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Dolly Sapra

Phd Student

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Julius Roeder

Phd Student

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Uraz Odyurt

Phd Student

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Merijn Verstraaten

Phd Student

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Jelle van Dijk

Phd Student

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Lukas Miedema

Phd Student

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Marius Herget

Phd Student

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Pooya Khandel

Phd Student

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Stephen Swatman

Phd Student

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Sudam Wasala

Phd Student

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Xiaotian Guo

Phd Student

Secretary

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Grace Millerson

Secretary

Alumni

Jun Xiao

Postdoctoral Researcher

Benjamin Rouxel

Postdoctoral Researcher

Sebastian Altmeyer

Assistant Professor

Giulio Stramondo

PhD student

Catalin Bogdan Ciobanu

Postdoctoral Researcher

Hugo Meyer

Postdoctoral Researcher

Thomas Bernard

PhD student

Cagkan Erbas

PhD student

Mark Thompson

PhD student

Michiel van Tol

PhD student

Mike Lankamp

PhD student

Peter van Stralen

PhD student

Raphael Poss

Postdoctoral Researcher

Roberta Piscitelli

PhD student

Roeland Douma

PhD student

Roy Bakker

PhD student

Toktam Taghavi

PhD student

Wei Quan

PhD student

Projects

APROPOS

Approximate Computing for Power and Energy Optimisation

TeamPlay

Time, Energy and security Analysis for Multi/Many-core heterogenous PLAtforms

ADMORPH

Towards Adaptively Morphing Embedded Systems

ALOHA

Software framework for runtime-Adaptive and secure deep Learning On Heterogeneous Architectures

DSE 2.0

Towards Optimal Design of Complex, Distributed Cyber Physical Systems

iDAPT

Interactive DSL for Composable EFB Adaptation using Bi-simulation and Extrinsic Coordination

Recent Publications

Julius Roeder, Benjamin Rouxel, Sebastian Altmeyer, Clemens Grelck (2021). Energy-aware Scheduling of Multi-version Tasks on Heterogeneous Real-time Systems. Proceedings of the 36rd Annual ACM Symposium on Applied Computing (SAC).

Dolly Sapra, Andy D. Pimentel (2020). Deep Learning Model Reuse and Composition in Knowledge Centric Networking. Proc. of the 29th International Conference on Computer Communications and Networks (ICCCN).

PDF DOI

Andy D. Pimentel (2020). A Case for Security-Aware Design-Space Exploration of Embedded Systems. Journal of Low Power Electronics and Applications.

PDF DOI

Ahmed Musaafir, Alexandru Uta, Henk Dreuning, Ana Lucia Varbanescu (2020). A Sampling-Based Tool for Scaling Graph Datasets. Proc. of the ACM/SPEC International Conference on Performance Engineering (ICPE).

PDF DOI

H. D. Meyer, U. Odyurt, A. D. Pimentel, Evangelos Paradas, Ignacio Gonzalez Alonso (2020). An Analytics-Based Method for Performance Anomaly Classification in Cyber-Physical Systems. The 35th ACM/SIGAPP Symposium On Applied Computing. SAC 2020.

DOI

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PCS Software

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All Deep Learning Simulators System Modeling

CoMeT

Core-memory thermal simulations for 2D, 2.5D, and 3D processors

HotSniper

Interval thermal simulation of 2D multi-/many-cores

Pipe-All

High-throughput CPU-GPU CNN inference pipeline

Sesame

High-level modeling and simulation of MPSoCs for early DSE

Synthetic Portnet Generator

for modeling software interfaces

Contact