How RAM Works.Pdf
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Modeling System Signal Integrity Uncertainty Considerations
WHITE PAPER Intel® FPGA Modeling System Signal Integrity Uncertainty Considerations Authors Abstract Ravindra Gali This white paper describes signal integrity (SI) mechanisms that cause system-level High-Speed I/O Applications timing uncertainty and how these mechanisms are modeled in the Intel® Quartus® Engineering, Intel® Corporation Prime software Timing Analyzer to achieve timing closure for external memory interface designs. Zhi Wong By using the Intel Quartus Prime software to achieve timing closure for external High-Speed I/O Applications memory interfaces, a designer does not need to allocate a separate SI timing Engineering, Intel Corporation budget to account for simultaneous switching output (SSO), simultaneous Navid Azizi switching input (SSI), intersymbol interference (ISI), and board-level crosstalk for Software Engineeringr flip-chip device families such as Stratix® IV and Arria® II FPGAs for typical user Intel Corporation implementation of external memory interfaces following good board design practices. John Oh High-Speed I/O Applications Introduction Engineering, Intel Corporation The widening performance gap between FPGAs, microprocessors, and memory Arun VR devices, along with the growth of memory-intensive applications, are driving the Memory I/O Applications Engineering, need for faster memory technologies. This push to higher bandwidths has been Intel Corporation accompanied by an increase in the signal count and the signaling rates of FPGAs and memory devices. In order to attain faster bandwidths, device makers continue to reduce the supply voltage. Initially, industry-standard DIMMs operated at 5 V. However, due to improvements in DRAM storage density, the operating voltage was decreased to 3.3 V (SDR), then to 2.5V (DDR), 1.8 V (DDR2), 1.5 V (DDR3), and 1.35 V (DDR3) to allow the memory to run faster and consume less power. -
Nanotechnology ? Nram (Nano Random Access
International Journal Of Engineering Research and Technology (IJERT) IFET-2014 Conference Proceedings INTERFACE ECE T14 INTRACT – INNOVATE - INSPIRE NANOTECHNOLOGY – NRAM (NANO RANDOM ACCESS MEMORY) RANJITHA. T, SANDHYA. R GOVERNMENT COLLEGE OF TECHNOLOGY, COIMBATORE 13. containing elements, nanotubes, are so small, NRAM technology will Abstract— NRAM (Nano Random Access Memory), is one of achieve very high memory densities: at least 10-100 times our current the important applications of nanotechnology. This paper has best. NRAM will operate electromechanically rather than just been prepared to cull out answers for the following crucial electrically, setting it apart from other memory technologies as a questions: nonvolatile form of memory, meaning data will be retained even What is NRAM? when the power is turned off. The creators of the technology claim it What is the need of it? has the advantages of all the best memory technologies with none of How can it be made possible? the disadvantages, setting it up to be the universal medium for What is the principle and technology involved in NRAM? memory in the future. What are the advantages and features of NRAM? The world is longing for all the things it can use within its TECHNOLOGY palm. As a result nanotechnology is taking its head in the world. Nantero's technology is based on a well-known effect in carbon Much of the electronic gadgets are reduced in size and increased nanotubes where crossed nanotubes on a flat surface can either be in efficiency by the nanotechnology. The memory storage devices touching or slightly separated in the vertical direction (normal to the are somewhat large in size due to the materials used for their substrate) due to Van der Waal's interactions. -
PATENT PLEDGES Jorge L. Contreras*
PATENT PLEDGES Jorge L. Contreras* ABSTRACT An increasing number of firms are making public pledges to limit the enforcement of their patents. In doing so, they are entering a little- understood middle ground between the public domain and exclusive property rights. The best-known of these patent pledges are FRAND commitments, in which patent holders commit to license their patents to manufacturers of standardized products on terms that are “fair, reasonable and non-discriminatory.” But patent pledges have been appearing in settings well beyond standard-setting, including open source software, green technology and the life sciences. As a result, this increasingly prevalent private ordering mechanism is beginning to reshape the role and function of patents in the economy. Despite their proliferation, little scholarship has explored the phenomenon of patent pledges beyond FRAND commitments and standard- setting. This article fills this gap by providing the first comprehensive descriptive account of patent pledges across the board. It offers a four-part taxonomy of patent pledges based on the factors that motivate patent holders to make them and the effect they are intended to have on other market actors. Using this classification system, it argues that pledges likely to induce reliance in other market actors should be treated as “actionable” * Associate Professor, S.J. Quinney College of Law, University of Utah and Senior Policy Fellow, American University Washington College of Law. The author thanks Jonas Anderson, Clark Asay, Marc Sandy Block, Mark Bohannon, Matthew Bye, Michael Carrier, Michael Carroll, Colleen Chien, Thomas Cotter, Carter Eltzroth, Carissa Hessick, Meredith Jacob, Jay Kesan, Anne Layne-Farrar, Irina Manta, Sean Pager, Gideon Parchomovsky, Arti Rai, Amelia Rinehart, Cliff Rosky, Daniel Sokol and Duane Valz for their helpful comments, suggestions and discussion of this article and contributions of data to the Patent Pledge Database at American University. -
AXP Internal 2-Apr-20 1
2-Apr-20 AXP Internal 1 2-Apr-20 AXP Internal 2 2-Apr-20 AXP Internal 3 2-Apr-20 AXP Internal 4 2-Apr-20 AXP Internal 5 2-Apr-20 AXP Internal 6 Class 6 Subject: Computer Science Title of the Book: IT Planet Petabyte Chapter 2: Computer Memory GENERAL INSTRUCTIONS: • Exercises to be written in the book. • Assignment questions to be done in ruled sheets. • You Tube link is for the explanation of Primary and Secondary Memory. YouTube Link: ➢ https://youtu.be/aOgvgHiazQA INTRODUCTION: ➢ Computer can store a large amount of data safely in their memory for future use. ➢ A computer’s memory is measured either in Bits or Bytes. ➢ The memory of a computer is divided into two categories: Primary Memory, Secondary Memory. ➢ There are two types of Primary Memory: ROM and RAM. ➢ Cache Memory is used to store program and instructions that are frequently used. EXPLANATION: Computer Memory: Memory plays a very important role in a computer. It is the basic unit where data and instructions are stored temporarily. Memory usually consists of one or more chips on the mother board, or you can say it consists of electronic components that store instructions waiting to be executed by the processor, data needed by those instructions, and the results of processing the data. Memory Units: Computer memory is measured in bits and bytes. A bit is the smallest unit of information that a computer can process and store. A group of 4 bits is known as nibble, and a group of 8 bits is called byte. -
Access Order and Effective Bandwidth for Streams on a Direct Rambus Memory Sung I
Access Order and Effective Bandwidth for Streams on a Direct Rambus Memory Sung I. Hong, Sally A. McKee†, Maximo H. Salinas, Robert H. Klenke, James H. Aylor, Wm. A. Wulf Dept. of Electrical and Computer Engineering †Dept. of Computer Science University of Virginia University of Utah Charlottesville, VA 22903 Salt Lake City, Utah 84112 Abstract current DRAM page forces a new page to be accessed. The Processor speeds are increasing rapidly, and memory speeds are overhead time required to do this makes servicing such a request not keeping up. Streaming computations (such as multi-media or significantly slower than one that hits the current page. The order of scientific applications) are among those whose performance is requests affects the performance of all such components. Access most limited by the memory bottleneck. Rambus hopes to bridge the order also affects bus utilization and how well the available processor/memory performance gap with a recently introduced parallelism can be exploited in memories with multiple banks. DRAM that can deliver up to 1.6Gbytes/sec. We analyze the These three observations — the inefficiency of traditional, performance of these interesting new memory devices on the inner dynamic caching for streaming computations; the high advertised loops of streaming computations, both for traditional memory bandwidth of Direct Rambus DRAMs; and the order-sensitive controllers that treat all DRAM transactions as random cacheline performance of modern DRAMs — motivated our investigation of accesses, and for controllers augmented with streaming hardware. a hardware streaming mechanism that dynamically reorders For our benchmarks, we find that accessing unit-stride streams in memory accesses in a Rambus-based memory system. -
Parallel Computer Architecture and Programming CMU / 清华 大学
Lecture 20: Addressing the Memory Wall Parallel Computer Architecture and Programming CMU / 清华⼤学, Summer 2017 CMU / 清华⼤学, Summer 2017 Today’s topic: moving data is costly! Data movement limits performance Data movement has high energy cost Many processors in a parallel computer means… ~ 0.9 pJ for a 32-bit foating-point math op * - higher overall rate of memory requests ~ 5 pJ for a local SRAM (on chip) data access - need for more memory bandwidth to avoid ~ 640 pJ to load 32 bits from LPDDR memory being bandwidth bound Core Core Memory bus Memory Core Core CPU * Source: [Han, ICLR 2016], 45 nm CMOS assumption CMU / 清华⼤学, Summer 2017 Well written programs exploit locality to avoid redundant data transfers between CPU and memory (Key idea: place frequently accessed data in caches/buffers near processor) Core L1 Core L1 L2 Memory Core L1 Core L1 ▪ Modern processors have high-bandwidth (and low latency) access to on-chip local storage - Computations featuring data access locality can reuse data in this storage ▪ Common software optimization technique: reorder computation so that cached data is accessed many times before it is evicted (“blocking”, “loop fusion”, etc.) ▪ Performance-aware programmers go to great effort to improve the cache locality of programs - What are good examples from this class? CMU / 清华⼤学, Summer 2017 Example 1: restructuring loops for locality Program 1 void add(int n, float* A, float* B, float* C) { for (int i=0; i<n; i++) Two loads, one store per math op C[i] = A[i] + B[i]; } (arithmetic intensity = 1/3) void mul(int -
Big Data, AI, and the Future of Memory
Big Data, AI, and the Future of Memory Steven Woo Fellow and Distinguished Inventor, Rambus Inc. May 15, 2019 Memory Advancements Through Time 1990’s 2000’s 2010’s 2020’s Synchronous Memory Graphics Memory Low Power Memory Ultra High Bandwidth for PCs for Gaming for Mobile Memory for AI Faster Compute + Big Data Enabling Explosive Growth in AI 1980s Annual Size of the Global Datasphere – 1990s Now 175 ZB More 180 Accuracy Compute Neural Networks 160 140 120 Other Approaches 100 Zettabytes 80 60 40 20 Scale (Data Size, Model Size) 2010 2015 2020 2025 Source: Adapted from Jeff Dean, “Recent Advances in Artificial Intelligence and the Source: Adapted from Data Age 2025, sponsored by Seagate Implications for Computer System Design,” HotChips 29 Keynote, August 2017 with data from IDC Global DataSphere, Nov 2018 Key challenges: Moore’s Law ending, energy efficiency growing in importance ©2019 Rambus Inc. 3 AI Accelerators Need Memory Bandwidth Google TPU v1 1000 TPU Roofline Inference on newer silicon (Google TPU K80 Roofline HSW Roofline v1) built for AI processing largely limited LSTM0 by memory bandwidth LSTM1 10 MLP1 MLP0 v nVidia K80 CNN0 Inference on older, general purpose Intel Haswell CNN1 hardware (Haswell, K80) limited by LSTM0 1 LSTM1 compute and memory bandwidth TeraOps/sec (log scale) (log TeraOps/sec MLP1 MLP0 CNN0 0.1 CNN1 LSTM0 1 10 100 1000 Memory bandwidth is a critical LSTM1 Ops/weight byte (log scale) resource for AI applications = Google TPU v1 = nVidia K80 = Intel Haswell N. Jouppi, et.al., “In-Datacenter Performance Analysis of a Tensor Processing Unit™,” https://arxiv.org/ftp/arxiv/papers/1704/1704.04760.pdf ©2019 Rambus Inc. -
Download Attachment
NON-CONFIDENTIAL 2010-1556 UNITED STATES COURT OF APPEALS FOR THE FEDERAL CIRCUIT ASUSTEK COMPUTER INC., ASUS COMPUTER INTERNATIONAL, INC., BFG TECHNOLOGIES, INC., BIOSTAR MICROTECH (U.S.A.) CORP., BIOSTAR MICROTECH INTERNATIONAL CORP., DIABLOTEK, INC., EVGA CORP., G.B.T., INC., GIGA-BYTE TECHNOLOGY CO., LTD., HEWLETT-PACKARD COMPANY, MSI COMPUTER CORP., MICRO-STAR INTERNATIONAL COMPANY, LTD., GRACOM TECHNOLOGIES LLC (FORMERLY KNOWN AS PALIT MULTIMEDIA, INC.), PALIT MICROSYSTEMS LTD., PINE TECHNOLOGY (MACAO COMMERCIAL OFFSHORE) LTD., AND SPARKLE COMPUTER COMPANY, LTD. Appellants, — v. — INTERNATIONAL TRADE COMMISSION, Appellee, and RAMBUS, INC., Intervenor, and NVIDIA CORPORATION, Intervenor. ______________ 2010-1557 ______________ NVIDIA CORPORATION, Appellant, — v. — INTERNATIONAL TRADE COMMISSION, Appellee, and RAMBUS, INC., Intervenor. ______________ ON APPEAL FROM THE UNITED STATES INTERNATIONAL TRADE COMMISSION IN INVESTIGATION NO. 337-TA-661 ______________ NON-CONFIDENTIAL REPLY BRIEF OF APPELLANTS NVIDIA CORPORATION ET AL. _______________ *Caption Continued on Next Page COMPANION CASES TO: 2010-1483 RAMBUS, INC., Appellant, — v. — INTERNATIONAL TRADE COMMISSION, Appellee, and NVIDIA CORPORATION ET AL., Intervenors. ______________ RUFFIN B. CORDELL I. NEEL CHATTERJEE MARK S. DAVIES ANDREW R. KOPSIDAS RICHARD S. SWOPE RACHEL M. MCKENZIE FISH & RICHARDSON P.C. NITIN GAMBHIR LAUREN J. PARKER 1425 K Street, NW, 11th Floor ORRICK, HERRINGTON ORRICK, HERRINGTON Washington, DC 20005 & SUTCLIFFE LLP & SUTCLIFFE LLP Tel. No. 202-626-6449 -
Unit 5: Memory Organizations
Memory Organizations Unit 5: Memory Organizations Introduction This unit considers the organization of a computer's memory system. The characteristics of the most important storage technologies are described in detail. Basically memories are classified as main memory and secondary memory. Main memory with many different categories are described in Lesson 1. Lesson 2 focuses the secondary memory including the details of floppy disks and hard disks. Lesson 1: Main Memory 1.1 Learning Objectives On completion of this lesson you will be able to : • describe the memory organization • distinguish between ROM, RAM, PROM, EEPROM and • other primary memory elements. 1.2 Organization Computer systems combine binary digits to form groups called words. The size of the word varies from system to system. Table 5.1 illustrates the current word sizes most commonly used with the various computer systems. Two decades ago, IBM introduced their 8-bit PC. This was Memory Organization followed a few years later by the 16-bit PC AT microcomputer, and already it has been replaced with 32- and 64-bit systems. The machine with increased word size is generally faster because it can process more bits of information in the same time span. The current trend is in the direction of the larger word size. Microcomputer main memories are generally made up of many individual chips and perform different functions. The ROM, RAM, Several types of semi- PROM, and EEPROM memories are used in connection with the conductor memories. primary memory of a microcomputers. The main memory generally store computer words as multiple of bytes; each byte consisting of eight bits. -
Open Poremba-Dissertation.Pdf
The Pennsylvania State University The Graduate School ARCHITECTING BYTE-ADDRESSABLE NON-VOLATILE MEMORIES FOR MAIN MEMORY A Dissertation in Computer Science and Engineering by Matthew Poremba c 2015 Matthew Poremba Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy May 2015 The dissertation of Matthew Poremba was reviewed and approved∗ by the following: Yuan Xie Professor of Computer Science and Engineering Dissertation Co-Advisor, Co-Chair of Committee John Sampson Assistant Professor of Computer Science and Engineering Dissertation Co-Advisor, Co-Chair of Committee Mary Jane Irwin Professor of Computer Science and Engineering Robert E. Noll Professor Evan Pugh Professor Vijaykrishnan Narayanan Professor of Computer Science and Engineering Kennith Jenkins Professor of Electrical Engineering Lee Coraor Associate Professor of Computer Science and Engineering Director of Academic Affairs ∗Signatures are on file in the Graduate School. Abstract New breakthroughs in memory technology in recent years has lead to increased research efforts in so-called byte-addressable non-volatile memories (NVM). As a result, questions of how and where these types of NVMs can be used have been raised. Simultaneously, semiconductor scaling has lead to an increased number of CPU cores on a processor die as a way to utilize the area. This has increased the pressure on the memory system and causing growth in the amount of main memory that is available in a computer system. This growth has escalated the amount of power consumed by the system by the de facto DRAM type memory. Moreover, DRAM memories have run into physical limitations on scalability due to the nature of their operation. -
DDR400/333/266, Dual DDR, RDRAM 16 Bit and 32 Bit, SDRAM
Ace’s Hardware Granite Bay: Memory Technology Shootout Granite Bay: Memory Technology Shootout By Johan De Gelas – December 2002 Dual-Channel DDR SDRAM Arrives for the Pentium 4 DDR400/333/266, Dual DDR, RDRAM 16 bit and 32 bit, SDRAM... almost every memory technology on the market is available for the Pentium 4 platform. One of our previous technical articles discussed the advantages and disadvantages of the different architectures of Rambus and SDRAM based memory technology such as DDR and DDR-II. In this article, we will investigate how the different memory technologies and their supporting chipsets compare on the test bench. The following motherboards were tested: • The ASUS P4T533 features the i850E chipset and 32 bit RDRAM • The ASUS P4T533-C comes with the same chipset but uses two channels of 16 bit RIMMs • The MSI 648 Max comes with SIS 648 chipset which unofficially supports DDR400 • The MSI i845PE comes with Intel's newest i845 chipset, which officially support DDR333 • The Tyan Trinity 7205 and MSI GNB Max feature the Dual DDR266 Granite Bay chipset We are well aware that there have already many tests with Pentium 4 chipsets, Granite Bay included. So why bother to publish another on Ace’s Hardware? The focus of this article is on the memory technology supported by these chipsets. This article will offer you a insight in how the different memory technologies compare in a wide variety of applications. We'll investigate in depth what the advantages and disadvantages are of each memory technology and try to find out what are the reasons behind this. -
Appendix to Brief of Appellee and Cross-Appellant Rambus Inc
PUBLIC UNITED STATES OF AMERICA BEFORE FEDERAL TRADE COMMISSION COMMISSIONERS: Deborah Platt Majoras, Chairman Orson Swindle Thomas B. Leary Pamela Jones Harbour Jon Leibowitz ) In the Matter of ) RAMBUS INCORPORATED, ) ) a corporation. ) Docket No. 9302 ) ) ) APPENDIX TO BRIEF OF APPELLEE AND CROSS-APPELLANT RAMBUS INC. Pursuant to the Commission’s October 4, 2004 Order granting Rambus leave to file an appendix, Rambus submits this appendix to its appeal brief containing a glossary of terms. -1- US1DOCS 4782131v1 Glossary of Terms Auto precharge: DRAMs store information as minute quantities of electrical charge in memory cells – no charge is interpreted as “0" and positive charge as a “1.” Sense amplifiers are circuits on the DRAM that sense the charge in a memory cell and amplify it when information is to be read from the DRAM. Before the sense amplifiers can perform this function, they must be “precharged” to an intermediate charged state. “Auto precharge” is a feature that was originally found in RDRAMs and later adopted by SDRAMs and DDR SDRAMs that allows the controller to determine whether the sense amplifiers are to be automatically precharged – that is, precharged without the need for a separate precharge command – at the end of a read or write operation. Bit/Byte: A bit or “binary digit” is the unit of information used by digital computers that takes on only two values – “0" or “1." Each memory cell in a DRAM stores a single bit. A “byte” usually refers to eight bits. Since each bit in a byte can take on two values, a byte can take on 28, or 256, possible values.