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Thermal Modeling and Management of Microprocessors

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Thermal Modeling and Management of Microprocessors Thermal Modeling and Management of Microprocessors A Dissertation Presented to the faculty of the School of Engineering and Applied Science University of Virginia In Partial Fulfillment of the requirements for the Degree Doctor of Philosophy Computer Science by Karthik Sankaranarayanan May 2009 Approvals This dissertation is submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Computer Science Karthik Sankaranarayanan Approved: Kevin Skadron (Advisor) Jack W. Davidson (Chair) 7 Mircea R. Stan (Co-Advisor) James P. Cohoon John Lach Accepted by the School of Engineering and Applied Science: April 2009 Abstract The most recent, and arguably one of the most difficult obstacles to the exponential growth in transistor density predicted by Moore’s Law is that of removing the large amount of heat generated within the tiny area of a microprocessor. The exponential increase in power density and its direct relation to on-chip temperature have, in recent processors, led to very high cooling costs. Since temperature also has an exponential effect on lifetime reliability and leakage power, it has become a first-class design constraint in microprocessor development akin to performance. This dissertation describes work to address the temperature challenge from the perspective of the architecture of the microprocessor. It proposes both the infrastructure to model the problem and several mechanisms that form part of the solution. This research describes HotSpot, an efficient and extensible microarchitectural thermal modeling tool that is used to guide the design and evalua- tion of various thermal management techniques. It presents several Dynamic Thermal Management (DTM) schemes that distribute heat both over time and space by controlling the level of compu- tational activity. Processor temperature is not only a function of the power density but also the placement and adjacency of hot and cold functional blocks, determined by the floorplan of the mi- croprocessor. Hence, this dissertation also explores various thermally mitigating placement choices available within a single core and across multiple cores of a microprocessor. It does so through the development of HotFloorplan, a thermally-aware microarchitectural floorplanner. Finally, through an analytical framework, this research also focuses on the spatial (size) granularity at which thermal management is important. If regions of very high power density are small enough, they do not cause hot spots. The granularity study quantifies this relationship and illustrates it using three different microarchitectural examples. iii Acknowledgments This dissertation would not have been possible without the help of so many people. I am greatly indebted to my advisor Professor Kevin Skadron for his guidance. His approach of giving me complete freedom has made me grow as an individual and take ownership of the research problem. He pushed me when he needed to and that is the reason I have reached this point of completion. A significant portion of the text of the second and third chapters of this dissertation arose out of a paper in which my advisor played the primary role in writing. I am also thankful to him for his flexibility in letting me work remotely so I could be with my wife and for his continued financial support all these years. This work was supported in part by the National Science Foundation under grant nos. CCR-0105626, CCR-0133634, EIA-0224434, CCF-0429765, CSR-0509245, CRI-0551630 and MIP-9703440, an Army Research Office grant no. W911NF-04-1-0288, an Excellence Award from the University of Virginia Fund for Excellence in Science and Technology, a grant from Intel MRL and an IBM Research Faculty Partnership Award. I am deeply grateful to my co-advisor Professor Mircea Stan for the countless hours of patient brainstorming. He helped me in grasping the circuit-level concepts right from the days when I was a student in his VLSI class. My sincere thanks to the members of my committee — apart from my advisor and co-advisor, Professors Jack Davidson, John Lach and James Cohoon, for their patient reading of my dissertation, considerate understanding of the change of scope of this work, will- ingness to give four crucial extra days for the submission of the dissertation and their constructive feedback that has helped in the shaping of this document. I am also thankful to Professor Hossein Haj-Hariri for teaching me the basics of analytical solutions of the heat equation and Professor Robert Ribando for directing me to the right person to ask such questions. I would also like to iv v express my thanks to Dr. Norman Jouppi for the discussion during his visit to UVA, which formed the origin of the L2 cache-bank insertion study. I have learnt much from my mentors during the two summer internships — Dr. Luiz Barroso and Dr. Scott McFarling and would like to thank them for the opportunity. I would also like to express my sincere thanks to all my professors and teachers, present and past, who have imparted the gift of knowledge in me. Many thanks to Intel and Dr. Daryl Nelson for the job offer and the patient wait. In these times of economic uncertainty, this security has helped me focus on my dissertation. I cannot thank my colleague Wei Huang enough for all his help. We have collaborated very closely and it is impossible to list the number of times I have benefited from Wei’s help in the form of explanations, experiments, feedback, reviews, code, text, figures etc. He is the primary contributor to the HotSpot thermal model. I would also like to convey my earnest appreciation for the contributions from Siva Velusamy, David Tarjan and Yingmin Li to the third chapter of this dissertation. Siva made important contributions to the implementation and evaluation of the DTM schemes. David calibrated the power model and Yingmin modified the performance model to mimic an Alpha-like architecture. I would also like to acknowledge the inputs of Siva to the modeling of the extra wire delay in the fourth chapter. I am thankful to Michele Co and Jeremy Sheaffer for their proposal and dissertation documents and presentations which served as samples to base mine upon. Many thanks to David Coppit and John Regehr for putting together a latex dissertation template conforming to the standards of UVA SEAS. I would like to express my thanks to my colleagues Michael Boyer, David Tarjan, Jiyauan Meng, Shuai Che, Eric Humenay and Yingmin Li for helping me work remotely by switching on my computer when it went down. Michael and David especially helped me by taking care of my office space and by plugging in my computer to the UPS. As an international student in a foreign country, my graduate life in UVA has benefited im- mensely from the help of many graduate students who have helped me in getting established during my initial years in Charlottesville. I would like to thank them all for all their help including the many rides and errands. I have been fortunate to have made and drawn support from many close friends formed during vi my stay at UVA, during the CEG days and during the high school days at Madurai. Many of them have become my extended family and I am extremely grateful for all their wishes and support. Among them, as my co-travellers in the Ph.D. journey, Ram, Sundar, Easwar and Lakshmi have been my sounding boards offering encouragement and sharing insights innumerable times. I am deeply indebted to them. I would not be here without my parents. Their constant belief in me, complete independence for my actions and respect for my choices have made me who I am. My heartfelt thanks to them for their love, blessings and prayers. I am thankful for my two little sisters’ wishes and untiring confidence in me. Preethi has been constantly cheering me since my middle school. Deepu has brought many laughs by sharing her youthful exploits. Many friends of our family have practically become part of our own over the years. I am thankful for all their wishes and blessings. I would also like to thank my relatives who took a lot of interest in my progress for their support. I have received invaluable guidance from two mentors in my personal life — my undergraduate advisor Professor Ranjani Parthasarathi and my uncle Mr. R. Mahendravel. RP ma’am, as we affectionately call her, has been an inspiration and an unending source of positive energy. My uncle has been a hero to me and has offered timely advice that has directed me in the right path many times in my life. I would like to express my deep gratitude for both of them. The last six months of dissertation research is similar to the last mile of a marathon. During this crucial time, my friend and brother, Ram, gave up many comforts in hosting us in his apartment. He would meditate for hours alongside of me when I was working on my dissertation. I am thankful beyond words for all his help, which has enabled my reaching this point. I am blessed to have a wonderful friend and wife in Meena. She has put her career on hold for a year just to be with me during this critical period. She has laughed with me during the successes and cried with me during the failures. She has been a provider of nourishment both in spirit and as actual food. She has been a part of me in this whole process. It is not possible to do justice by expressing my thanks to her in words. vii The entire process of dissertation research has been both an exercise in confidence and an ex- ercise in humility. I thank the experience itself, for it was built of many life lessons.
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