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Performance Analysis of Application-Specific Multicore Systems on Chip

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Performance Analysis of Application-Specific Multicore Systems on Chip Royal Institute of Technology Performance Analysis of Application-Specific Multicore Systems on Chip Iyad Al Khatib A thesis submitted to The Royal Institute of Technology in partial fulfillment of the requirements for the degree of Doctor of Technology June 13, 2008 Department of Electronic, Computer, and Software Systems (ECS) School of Information and Communication Technology (ICT) Royal Institute of Technology (KTH) Stockholm, Sweden Al Khatib, Iyad Performance Analysis of Application-Specific Multicore Systems on Chip Doctoral Thesis in Electronic and Computer Systems Department of Electronic, Computer, and Software Systems (ECS) School of Information and Communication Technology (ICT) Royal Institute of Technology (KTH) TRITA-ICT/ECS AVH 08:06 ISSN 1653-6363 ISRN KTH/ICT/ECS/ AVH-08/06--SE ISBN 978-91-7178-960-0 KTH/ICT/ECS: Electronic, Computer, and Software Systems Royal Institute of Technology Isafjordsgatan 39 P.O. Box Forum 120 SE-164 40 Kista Sweden Copyright Iyad Al Khatib, June 13, 2008 ii ABSTRACT The last two decades have witnessed the birth of revolutionary technologies in data communications including wireless technologies, System on Chip (SoC), Multi Processor SoC (MPSoC), Network on Chip (NoC), and more. At the same time we have witnessed that performance does not always keep pace with expectations in many services like multimedia services and biomedical applications. Moreover, the IT market has suffered from some crashes. Hence, this triggered us to think of making use of available technologies and developing new ones so that the performance level is suitable for given applications and services. In the medical field, from a statistical viewpoint, the biggest diseases in number of deaths are heart diseases, namely Cardiovascular Disease (CVD) and Stroke. The application with the largest market for CVD is the electrocardiogram (ECG/EKG) analysis. According to the World Health Organization (WHO) report in 2003, 29.2% of global deaths are due to CVD and Stroke, half of which could be prevented if there was proper monitoring. We found in the new advance in microelectronics, NoC, SoC, and MPSoC, a chance of a solution for such a big problem. We look at the communication technologies, wireless networks, and MPSoC and realize that many projects can be founded, and they may affect people's lives positively, as for example, curing people more rapidly, as well as homecare of such large scale diseases. These projects have a medical impact as well as economic and social impacts. The intention is to use performance analysis of interconnected microelectronic systems and combine it with MPSoC and NoC technologies in order to evolve to new systems on chip that may make a difference. Technically, we aim at rendering more computations in less time, on a chip with smaller volume, and with less expense. The performance demand and the vision of having a market success, i.e. contributing to lower healthcare costs, pose many challenges on the hardware/software co-design to meet these goals. This calls upon the development of new integrated circuits featuring increased energy efficiency while providing higher computation capabilities, i.e. better performance. The biomedical application of ECG analysis is an ideal target for an application-specific SoC implementation. However, new 12-lead ECG analyses algorithms are needed to meet the aforementioned goals. In this thesis, we present two novel algorithms for ECG analysis, namely the Autocorrelation-Function (ACF) based algorithm and the Fast Fourier Transform (FFT) based algorithm. In this respect, we explore the design space by analyzing different hardware and software architectures. As a result, we realize a design with twelve processors that can compute 3.5 million arithmetic computations and respect the real time hard deadline for our biomedical application (3.5-4 seconds), and that can deploy the ACF-based and FFT-based algorithms. Then, we investigate the configuration space looking for the most effective solution, performance and energy-wise. Consequently, we present three interconnect architectures (Single Bus, Full Crossbar, and Partial Crossbar) and compare them with existing solutions. The sampling frequencies of 2.2 KHz and 4 KHz, with 12 DSPs, are found to be the critical points for our Shared-Bus design and Crossbar architecture, respectively. We also show how our performance analysis methods can be applied to such a field of SoC design and with a specific purpose application in order to converge to a solution that is acceptable from a performance viewpoint, meets the real-time demands, and can be implemented with the present technologies while at the same time paving the way for easier and faster development. In order to connect our MPSoC solution to communication networks to transmit the medical results to a healthcare center, we come up with new protocols that will allow the integration of multiple networks on chips in a communication network. Finally, we present a methodology for HW/SW Codesign for application-specific systems (with focus on biomedical applications) that require a large number of computations since this will foster the convergence to solutions that are acceptable from a performance point of view. iii ACKNOWLEDGMENTS “He who does not seek advice is a fool. His folly blinds him to Truth and makes him evil, stubborn and a danger to his fellow man.” Joubran Khalil Joubran- known also as Kahlil Gibran ( 1883 – 1931 A.D.) Firstly, I would like to thank my advisor, Professor Axel Jantsch, whom I would simply describe as one of the greatest advisors I have ever seen for his knowledge, understanding, logic, and ease of cooperation. I thank Professor Axel from the bottom of my heart, for without him, surely and truly this thesis would not have existed. I thank Dr. Robert Ronngren for his help and support all the time. Also many thanks are to Prof. Slimane Ben Slimane for the fruitful help and the nice talks. Special thanks are to Professor Luca Benini, whom I enjoy working with and learning from. In addition, I thank my friend professor Davide Bertozzi for creating a wonderful atmosphere at work. I have learned a lot from him, so I thank him for that! I thank Francesco Poletti for the great working days we spent in Italy. Infinite thanks are not enough for the great rose and wonderful person who never left me at any second of my hard and good times, Ms. Marilet De Andrade Jardin. Thank you very much for all the support, and I think that even if I give you everything I could, that won’t be enough to really thank you for the amount of love, support and sweetness you showed. Special Thanks to my great friends Lennart Johansson, Victor Kordas, and Anders Nilsson, without whom I could not finish this thesis. Their understanding was very important! Many thanks go to Mr. Peter Ekman, Mr. Kaj Mikkos, and Ms. Paola Diaz whose support from ALMI for my patents was so great and unforgettable! Thank you very much! Thanks to Dr. Luc Onana Alima and his family for all the good times and the support. I also thank my friend Miguel Simon for the great work times and the wonderful laughs! Also I thank my friend Moustafa Chenine for the support and the good chats and advice. I also thank my friend Wim Michielsen for his advice and for being always supportive. I also thank all my friends, whose support was essential to finish this thesis. Special thanks to Katherine Stuart, whose love and support especially in my first few years in Sweden were basic for my success in many things including this thesis. I thank my brother Bassam Kayal for words can not describe how I trust him and count on him in most of my work and life issues especially in Sweden. I thank Bassam and his brothers and sisters, and mainly Mehdi and Adnan for the wonderful, fruitful and supportive chats and meetings! I also thank Zaidoon Jabbar, who was available to help me all the time! Moreover, I thank Mr. Khaled Khalil and his wonderful family. Khaled was very helpful and even just talking to him and getting his support saved me from wasting much of my time. Thank you very much Khaled to you and your understanding family! Many thanks are for Mohammad Saleh, who has helped me in many of my work issues in research and in many life matters. I will never forget the hard times that we went through together and also the nice good laughs. I thank my brother Nicolas Baron so much since, honestly, his presence in the hardest times of my life was the reason why I survived well. Many thanks fly to my brother Xavier Jombart and his beautiful lady Therese. I also thank my brother Giuseppe Russo for all his support and understanding. Special thanks to his family, his father Franco, his mother Franca, and his brother and all his uncles and aunts. With them, I always feel that I am with my family! Special thanks to the wonderful Calabria and Calabrians! Giuseppe remains in a very special place in my heart always! I thank also Dr. Carlo Spellucci, the traveling brother, iv and all his family. Many thanks for the great help many times. I thank Dr. Fabio Curti for all the help and for being an excellent brother and friend. Thanks to Prof. Maurizio Di Ruscio and Prof. Carlo Uliveiri, who are excellent friends and researchers! Discussions with them led to endless ideas for me! Thanks to Francesco as well! Thanks to my brother Diego for his emails in science and in social affairs. Many thanks to my brother Nunzio Giovinazzi for his great support and wonderful laughs and time spent together! I also thank my friend Oscar Alcamo for the wonderful time we spent together! I thank Christine Ardini for the wonderful chats we had while in the lab in Italy.
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