PPT-A Fast Flexible Simulation Platform for Multi-Core Systems

Committee Members Dr Abu Asaduzzaman Dr Ravi Pendse Dr Mehmet Bayram Yildirim Phanendra S N Gavara Outline Problem description Thesis contributions Why simulation technique. All Flexible Core courses must me et the following three learning outcomes A student will x Gather interpret and assess information from a v ariety of sources and points of view x Evaluate evidence and arguments critically or analytically x Produce Zach ma. ADVISOR: MUNEHIRO FUKUDA. M. ulti-Agent Transportation Simulation Using MASS. MATMASSim. What Is Transportation Simulation?. Microscopic. . Car-following model. Macroscopic. . Traffic flow model. In Action. The comScore Roadmap for Multi-Platform Cross-Media Measurement and Results of the CIMM Study. Joan FitzGerald, SVP, Television and Cross-Media Solutions. It’s Simple, . RIGHT?. How Many?. 1 Research Engineer, WSL Swiss Federal Institute of Snow and Avalanche Research (SLF), Fl 2. Processor development till 2004. Out-of-order. Instruction scheduling. 3. Why multi-core ?. Difficult to make single-core. clock frequencies even . higher – heat problems . Deeply pipelined circuits:. laws . and . architectures:. Theory and lessons from. nets, grids, brains, bugs,. . planes, docs, fire, fashion,. art, turbulence, music, buildings, . cities, earthquakes, bodies, running, throwing, . 道陽. Jean-Lou Chameau Professor. Control and Dynamical Systems, EE, & . BioE. tech. 1. #. Ca. Universal laws . and architectures. :. Theory and lessons. . from. brains, bugs,. . nets, grids, . 2. Processor development till 2004. Out-of-order. Instruction scheduling. 3. Why multi-core ?. Difficult to. increase. . clock . frequencies even . higher – heat . problems. . Moore’s law is at its limits. Dr. . Feng Gu. Weather Prediction Example. Possible models to predict the weather tomorrow. . 1. Mystery-based models . (e.g., whenever my right eyelid twitches, it is going to rain tomorrow) . Haiqing. . Guo. 1. , Marcos Vanella. 2. , Sean Crowley. 1. , . Paul . Scrofani. 1. , . Richard E. . Lyon. 1. 1. . William J. Hughes Technical Center, FAA, Atlantic City, NJ. 2. NIST, Gaithersburg, NJ. Jaeung Han¹, Jeongseob Ahn¹, . Changdae. Kim. ¹, Youngjin Kwon¹, . Young-. ri. Choi², and Jaehyuk Huh¹. ¹ KAIST. (Korea Advanced Institute of Science and Technology). ² KISTI. (Korea Institute of Science and Technology Information). Navaneet Kumar, Sandeep Jain, Rajesh Jain. Networking & Multimedia Solutions Group. Updated Jan 2012. Outline. Virtual Platform – Challenges & Requirement. Significance of TLM 2.0. TLM LT Methodology. PURPOSE- convey broad view of process sequence. Actual 4-cm drive tube extrusions were performed inside a nitrogen glovebox with more refined . equipment. Refer to SPP 70 for exact procedure. J Allton. Out-of-order. Instruction scheduling. 3. Why multi-core ?. Difficult to make single-core. clock frequencies even . higher – heat problems . Deeply pipelined circuits:. heat . problems, needs special cooling arrangements.