PPT-1 Multiprocessor

and RealTime Scheduling Chapter 10 RealTime scheduling will be covered in SYSC3303 2 Classifications of Multiprocessor Loosely coupled or distributed multiprocessor or cluster each processor has its own memory and IO channels. 1 Multiprocessor System Interconnects Generalized Multiprocessor System Generalized Multiprocessor System Each processor Pi is attached to its own local memory and private cache Multiple processors connected to shared memory through interprocessor me For each of the approaches the associated protocol is outlined The simulation model is described and results from that model are presented The magnitude of the potential performance difference between the various approaches indicates that the choice 142 brPage 2br Taxonomy SISD single instruction and sing le data stream uniprocessor MISD no commercial multiprocessor imagine data going through a pipeline of execution engines SIMD vector architectures lower flexibility MIMD most multiprocessors to coprocessor 8087 2 closely coupled 8089 3 loosely coupled Multibus Coprocessors and closely coupled configurations are similar in that both the CPU and the external processor share Memory IO system Bus bus control logic Clock generator Closely Tullsen University of California San Diego asvenkattullsencsucsdedu Abstract Heterogeneous multicore architectures have the potential for high performance and energy ef64257ciency These architec tures may be composed of small poweref64257cient cores Håkon Kvale . Stensland. iAD-lab, Department for Informatics. Basic 3D Graphics Pipeline. Application. Scene Management. Geometry. Rasterization. Pixel Processing. ROP/FBI/Display. Frame. Buffer. Memory. James H. Anderson. University of North Carolina at Chapel Hill. November 2010. Outline. What. …. is LITMUS. RT. ?. Why. …. was LITMUS. RT. developed?. How. …. do we use LITMUS. RT. ?. Which. The Art of Multiprocessor Programming. by Maurice Herlihy & . Nir. . Shavit. Concurrent Skip Lists. 2. Set Object Interface. Collection of elements. No duplicates. Methods. add(). a new element. Companion slides for. The Art of Multiprocessor Programming. by Maurice Herlihy & Nir Shavit. Art of Multiprocessor Programming. 2. Focus so far: Correctness and Progress. Models. Accurate . (we never lied to you). The Art of Multiprocessor Programming. by Maurice Herlihy & Nir Shavit. Art of Multiprocessor Programming. 2. Review: . Amdahl. '. s . Law. Speedup =. Shared Data Structures. 75%. Unshared. 25%. Shared. Companion slides for. The Art of Multiprocessor Programming. by Maurice Herlihy & Nir Shavit. Art of Multiprocessor Programming. 2. Shared-Memory Computability. Mathematical model of . concurrent. Companion slides for. The Art of Multiprocessor Programming. by Maurice Herlihy & Nir Shavit. Art of Multiprocessor Programming. 2. A Shared Pool. Put. Insert item. block if full. Remove. Remove & return item. Companion slides for. The Art of Multiprocessor Programming. by Maurice Herlihy & Nir Shavit. Art of Multiprocessor Programming. 2. Last Lecture: Spin-Locks. CS. Resets lock . upon exit. spin . lock. Companion slides for. The Art of Multiprocessor Programming. by Maurice Herlihy & Nir Shavit. Art of Multiprocessor Programming. 2. 2. The Five-Fold Path. Coarse-grained locking. Fine-grained locking.