PPT-Memory Optimizations

Research at UNT Krishna Kavi Professor Director of NSF IndustryUniversity Cooperative Center for NetCentric Software and Systems NetCentric IUCRC Computer Science and Engineering The University of North Texas. Bruce Worthington. Software Development Manager. Microsoft Corporation. Key Takeaways. Be a leader in advancing 64-bit computing. Adopt best practices and new tools. Let’s partner on new hardware directions. : Rethinking the Multicore Memory Hierarchy. for Disciplined Parallelism. Byn Choi, Rakesh Komuravelli, . Hyojin Sung. , . Robert Smolinski, . Nima. . Honarmand. , . Sarita. V. Adve, . Vikram. S. Adve, Nicholas P. Carter, Ching-Tsun Chou. Chapter . 2. Memory Hierarchy Design. Computer Architecture. A Quantitative Approach, Fifth Edition. Copyright © 2012, Elsevier Inc. All rights reserved.. Introduction. Programmers want . very large memory . The material in these slides has been taken from the NVIDIA manuals (Best Practices Guide & Optimizing Matrix Transpose in CUDA), and from a paper by . Ryoo. et al [Ryoo12]. See "A bit of History" in the last slide. Processing . on OpenCL-based FPGAs. Zeke Wang. , Johns Paul, Hui Yan Cheah . (. NTU,. . Singapore), . Bingsheng He (. NUS,. Singapore), . Wei Zhang (HKUST, Hong Kong). 1. Outline. Background and Problem. By Namita Dave. Overview. What are compiler optimizations?. Challenges with optimizations. Current Solutions. Machine learning techniques. Structure of Adaptive compilers. Introduction. O. ptimization . Prof. O. . Nierstrasz. Lecture notes by Marcus . Denker. © Marcus . Denker. Optimization. Roadmap. Introduction. Optimizations in the Back-end. The Optimizer. SSA Optimizations. Advanced Optimizations. Ross Tate. Michael Stepp. Sorin Lerner. University of California, San Diego. Optimizing by Hand. Original. for (i = 0; i < 50; i ). . for (j = 0; j < 50; j ). . img[i*50 j] = f(i, j);. .pptx: http://. tinyurl.com/6y7gy8x (or scan QR code). The . paper: http. ://dl.acm.org/citation.cfm?id=1122414. [1] . http://. www.nic.uoregon.edu/iwomp2005/IWOMP_Photos_Day1/IWOMP_Photos-Images/7.jpg. Chapter . 2. Memory Hierarchy Design. Computer Architecture. A Quantitative Approach. , Sixth Edition. Copyright © 2019, Elsevier Inc. All rights Reserved. Introduction. Programmers want unlimited amounts of memory with low latency. tool . and parallelization. do {. //get the write lock. . KeAcquireSpinLock. (&. devExt. ->. writeListLock. );. . nPacketsOld. = . nPackets. ; . request = . devExt. ->. WriteListHeadVa. Lecture for CPSC 5155. Edward Bosworth, Ph.D.. Computer Science Department. Columbus State University. The Simple View of Memory. The simplest view of memory is . that presented . at the ISA (Instruction Set Architecture) level. At this level, memory is a . T. Chen, T. Moreau, Z. Jiang, L. Zheng, S. Jiao, E. Yan, H. Shen, M. Cowan, L. Wang, Y. Hu, L. . Ceze. , C. . Guestrin. , and A. Krishnamurthy . Presentation by Grzegorz . Cued Recall. Recognition. Savings. Implicit / Indirect Memory. Procedural Memory. Declarative Memory. The Information Processing View of Memory. Short Term Memory. Long Term Memory. Episodic Memory. Source Amnesia.