PPT-Multiprocessing Linear Speedup

Basic Multiprocessor Centralizedmemory multiprocessor Distributedmemory multiprocessor Invalid Based Cache Coherence Protocol Processor 1 Processor 2 Processor 3 Event 0 No Copy No Copy No copy . g 03 Canonical example GPUs MIMD Multiple Instruction Multiple Data Ie 2 or more semiindependent CPUS 3 13 SIMD and MIMD Multiple CPUs come in several 64258avors SIMD Single Instruction Multiple Data Also called vector processor Sample instruction a . Parallel Speedup Estimates for Serial Programs. Donghwan. . Jeon. , . Saturnino. Garcia, Chris. Louie, . and Michael Bedford Taylor. Computer Science and Engineering. University of California, San Diego. What we sort of assumed so far…. Northbridge connects CPU and memory to rest of system. Memory controller implemented in Northbridge chipset. Devices and CPU can access memory via requests to Northbridge. Chak. Yee. How are SSDs involved?. File I/O slowest when seeking and writing to hard drive.. SSDs don’t have platters or mechanical heads, thus eliminates seek time.. . Single vs. Multithreaded Read. : . A . Toolchain. To Help Parallel Programming . Minjang Kim, Hyesoon Kim, . HPArch. Lab, and Chi-Keung . Luk. Intel. This work will be also supported by Samsung. Motivation (1/2). Parallel programming is hard. Module Ali Alzabarah 4 3 2 1 Introduction Python and concurrency Multiprocessing VS Threading Multiprocessing module 8 7 6 5 Pool of worker Distributed concurrency Credit when credit is due Reference Duo-core processors . What is Multiprocessing?. The use of more than one Central Processing Unit (CPU) with a single computer system, to perform tasks.. In multiprocessing most if not all CPUs perform the same function, however some may be reserved for a different function.. Through . Barrier-Interval Time-Parallelism . Paul D. Bryan, . Jason A. . Poovey. , Jesse G. . Beu. , Thomas M. . Conte. Georgia Institute of Technology. Outline. Introduction. Multi-threaded Application Simulation Challenges. We will use a quantitative approach to analyze architectures and potential improvements and see how well they work (if at all). We study RISC instruction sets to promote instruction-level, block-level and thread-level parallelism. Shuochao Yao, Yiwen Xu, Daniel Calzada. Network Compression and Speedup. 1. Source: . http://isca2016.eecs.umich.edu/. wp. -content/uploads/2016/07/4A-1.pdf. Network Compression and Speedup. 2. Why smaller models?. Sameera K. Abeykoon. Meifeng Lin. Kerstin Kleese van Dam. Talk outline. Scikit- beam. X-ray Photon. correlation Spectroscopy (XPCS). One-time correlation. . Two-time. quantitative approach to analyze architectures and potential improvements and see how well they work. We study RISC instruction sets to promote . instruction-level, block-level and thread-level parallelism. Performance of Computer System. Various factors. Depends on. Scalability: . Computer Performance . Number of processors used. Measuring performance of parallel computer architecture for large-scale applications require very good understanding of... http://www.cse.iitk.ac.in/~mainakc/lockfree.html. Prabhakar. . Misra. and . Mainak. Chaudhuri. Indian Institute of Technology, Kanpur. Sketch. Talk in one slide. Result highlights. Related work. Lock-free data structures.