Tools and Benchmarks for Real-Time Systems

2019 industrial challenge • Re: Amalthea Model of the Industrial Challenge 2019

2019-10-04T13:05:42+01:00

I am happy to announce the Amalthea model describing the application presented in the Industrial Challenge 2019. Please read the description for details about the application and the modelling concepts. We also provide a small Amalthea example model (CPU_Mapping_Changes) illustrating the transformations involved when moving a task from the GPU to a CPU.
The task "Planner" is activated every 12 ms but its execution time is higher than 12 ms for the A57 and the Denver.
Therefore please change the period of the task (stimuli in the Amalthea model) to 15ms.

I uploaded a model that incorporates this fix (top of the page).

Statistics: Posted by arne.hamann — Fri Oct 04, 2019

2019 industrial challenge • Re: Amalthea Model of the Industrial Challenge 2019

2019-08-29T09:24:34+01:00

I am happy to announce the Amalthea model describing the application presented in the Industrial Challenge 2019. Please read the description for details about the application and the modelling concepts. We also provide a small Amalthea example model (CPU_Mapping_Changes) illustrating the transformations involved when moving a task from the GPU to a CPU.

The task "Planner" is activated every 12 ms but its execution time is higher than 12 ms for the A57 and the Denver.
Therefore please change the period of the task (stimuli in the Amalthea model) to 15ms.

Statistics: Posted by Falk — Thu Aug 29, 2019

2019 industrial challenge • Re: Challenge 2019 Solution #2: Combined Data Transfer Response Time and Mapping Exploration in MPSoCs

2019-07-29T10:25:39+01:00

Dear all,

please excuse the late upload of the slides presented at the WATERS'19 workshop. They are attached.
Note that slide 5 and 7 originally contained animations, so please excuse the slighly wrong layout.

Best regards,

Alexander Diewald

waters2019.pdf

Statistics: Posted by Alexander_Diewald — Mon Jul 29, 2019

2019 industrial challenge • Re: Challenge 2019 Solution #3: An analytical approach for calculating end-to-end response times in autonomous driving a

2019-07-15T09:38:50+01:00

Dear all,

please find attached the slides of our presentation.

Best regards,

Lukas

20190709_WATERS2019.pdf

Statistics: Posted by lukas.krawczyk — Mon Jul 15, 2019

2019 industrial challenge • Re: Challenge 2019 Solution #2: Combined Data Transfer Response Time and Mapping Exploration in MPSoCs

2019-06-26T19:56:26+01:00

Dear all,

please find our approach to address the challenge in the attached pdf file.
Also, a big thanks to the organizers for all the efforts and provisioning the challenge.

Best regards,

Alexander Diewald, Simon Barner and Selma Saidi

FinalVersion.pdf

Statistics: Posted by Alexander_Diewald — Wed Jun 26, 2019

2019 industrial challenge • Re: Challenge 2019 Solution #3: An analytical approach for calculating end-to-end response times in autonomous driving a

2019-06-26T13:51:08+01:00

Dear all,

Please find attached our contribution to the WATERS2019 challenge.

Best Regards,
Lukas Krawczyk, Mahmoud Bazzal, Ram Prasath Govindarajan and Carsten Wolff

paper_final.pdf

Statistics: Posted by lukas.krawczyk — Wed Jun 26, 2019

2019 industrial challenge • Re: Challenge 2019 Solution #1: CPU-GPU Response Time and Mapping Analysis for High-Performance Automotive Systems

2019-06-26T10:11:38+01:00

Hi everyone,

please find attached our paper addressing the WATERS2019 challenge.
We hope you do not mind the additional (seventh) page.

Looking forward to meeting you in Stuttgart and best regards,
Robert

waters19_CPU-GPU_final.pdf

Statistics: Posted by robert — Wed Jun 26, 2019

2019 industrial challenge • Re: Challenge 2019 Solution #4: Addressing Analysis and Partitioning issues for the WATERS 2019 Challenge

2019-06-25T15:58:32+01:00

Dear all,

Please find attached our contribution to the WATERS 2019 Challenge.

Best Regards,
Daniel Casini, Paolo Pazzaglia, Alessandro Biondi, Giorgio Buttazzo and Marco Di Natale

WATERS2019_Final.pdf

Statistics: Posted by d.casini — Tue Jun 25, 2019

2019 industrial challenge • Challenge 2019 Solution #4: Addressing Analysis and Partitioning issues for the WATERS 2019 Challenge

2019-06-17T12:06:04+01:00

Title: Addressing Analysis and Partitioning issues for the WATERS 2019 Challenge
Authors: Daniel Casini, Paolo Pazzaglia, Alessandro Biondi, Giorgio Buttazzo and Marco Di Natale

Statistics: Posted by pagetti — Mon Jun 17, 2019

2019 industrial challenge • Challenge 2019 Solution #3: An analytical approach for calculating end-to-end response times in autonomous driving appli

2019-06-17T12:02:36+01:00

Title: An analytical approach for calculating end-to-end response times in autonomous driving applications
Authors: Lukas Krawczyk, Mahmoud Bazzal, Ram Prasath Govindarajan and Carsten Wolff

Statistics: Posted by pagetti — Mon Jun 17, 2019

2019 industrial challenge • Challenge 2019 Solution #2: Combined Data Transfer Response Time and Mapping Exploration in MPSoCs

2019-06-17T11:57:54+01:00

Title: Combined Data Transfer Response Time and Mapping Exploration in MPSoCs
Authors: Alexander Diewald, Simon Barner and Selma Saidi

Statistics: Posted by pagetti — Mon Jun 17, 2019

2019 industrial challenge • Challenge 2019 Solution #1: CPU-GPU Response Time and Mapping Analysis for High-Performance Automotive Systems

2019-06-17T11:54:56+01:00

Title CPU-GPU Response Time and Mapping Analysis for High-Performance Automotive Systems
Authors Robert Hoettger, Junhyung Ki, The Bao Bui, Burkhard Igel and Olaf Spinczyk

Statistics: Posted by pagetti — Mon Jun 17, 2019

Regular contributions • Evaluation Framework for Self-Suspending Task Systems

2019-05-29T13:55:22+01:00

Title: Evaluation Framework for Self-Suspending Task Systems

Authors: Georg von der Brüggen, Milad Nayebi, Junjie Shi, Kuan-Hsun Chen and Jian-Jia Chen

Abstract:

WATERS_2019_paper_8.pdf

Statistics: Posted by pagetti — Wed May 29, 2019

Regular contributions • A time, energy and security coordination approach

2019-05-29T13:49:58+01:00

Title: A time, energy and security coordination approach

Authors: Benjamin Rouxel, Julius Roeder, Sebastian Altmeyer and Clemens Grelck

Abstract:

WATERS_2019_paper_1.pdf

Statistics: Posted by pagetti — Wed May 29, 2019

Regular contributions • Machine Learning Based Cross-Platform Runtime Prediction

2019-05-29T13:43:48+01:00

Title: Machine Learning Based Cross-Platform Runtime Prediction

Authors: Ahsan Saeed, Falk Wurst, Michael Pressler, Arne Hamann and Dakshina Dasari

Abstract:

WATERS_2019_paper_2.pdf

Statistics: Posted by pagetti — Wed May 29, 2019