Time, Energy and Security Analysis for Multi-/Many-Core heterogeneous Platforms (TeamPlay)
|Name||Time, Energy and Security Analysis for Multi-/Many-Core heterogeneous Platforms|
|Role of TUHH||Work Package Leader|
|Funds Donor||European Commission (Horizon 2020)|
The TeamPlay project aims to develop new, formally-motivated, techniques that will allow execution time, energy usage, security, and other important non-functional properties of parallel software to be treated effectively, and as first-class citizens. We will build this into a toolbox for developing highly parallel software for low-energy systems, as required by the internet of things, cyber-physical systems etc. The TeamPlay approach will allow programs to reflect directly on their own time, energy consumption, security, etc., as well as enabling the developer to reason about both the functional and the non-functional properties of their software at the source code level.
Our success will ensure significant progress on a pressing problem of major industrial importance: how to effectively manage energy consumption for parallel systems while maintaining the right balance with other important software metrics, including time, security etc. The project brings together leading industrial and academic experts in parallelism, energy modeling/transparency, worst-case execution time analysis, non-functional property analysis, compilation, security, and task coordination. Results will be evaluated using industrial use cases taken from the computer vision, satellites, flying drones, medical and cybersecurity domains.
TeamPlay Publications of the Embedded Systems Design Group
|Title: Compiling for the Worst Case: Memory Allocation for Multi-task and Multi-core Hard Real-time Systems.|
|Written by: Arno Luppold, Dominic Oehlert and Heiko Falk|
|in: <em>ACM Transactions on Embedded Computing Systems (TECS)</em>. March (2020).|
|Volume: <strong>19</strong>. Number: (2),|
|how published: 20-95 LOF20 TECS|
Note: aluppold, doehlert, hfalk, ESD, multiopt, teamplay, WCC
Abstract: Modern embedded hard real-time systems feature multiple tasks running on multiple processing cores. Schedulability analysis of such systems is usually performed on an abstract system level with each task being represented as a black box with fixed timing properties. If timing constraints are violated, optimizing the system on a code-level in order to achieve schedulability is a tedious task. To tackle this issue, we propose an extension to the WCET-Aware C Compiler framework WCC. We integrated an optimization framework based on Integer-Linear Programming into the WCC which is able to optimize a multi-core system with multiple tasks running on each core with regards to its schedulability. We evaluate the framework by providing two approaches on a schedulability aware static Scratchpad Memory (SPM) allocation: One based on Integer-Linear Programming (ILP) and one based on a genetic algorithm.