A VHDL Model of a Superscalar Implementation of the DLX Instruction Set Architcture
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GPU Implementation Over IPTV Software Defined Networking
Esmeralda Hysenbelliu. Int. Journal of Engineering Research and Application www.ijera.com ISSN : 2248-9622, Vol. 7, Issue 8, ( Part -1) August 2017, pp.41-45 RESEARCH ARTICLE OPEN ACCESS GPU Implementation over IPTV Software Defined Networking Esmeralda Hysenbelliu* Information Technology Faculty, Polytechnic University of Tirana, Sheshi “Nënë Tereza”, Nr.4, Tirana, Albania Corresponding author: Esmeralda Hysenbelliu ABSTRACT One of the most important issue in IPTV Software defined Network is Bandwidth Issue and Quality of Service at the client side. Decidedly, it is required high level quality of images in low bandwidth and for this reason it is needed different transcoding standards (Compression of image as much as it is possible without destroying the quality of it) as H.264, H265, VP8 and VP9. During a test performed in SMC IPTV SDN Cloud Network, it was observed that with a server HP ProLiant DL380 g6 with two physical processors there was not possible to transcode in format H.264 more than 30 channels simultaneously because CPU’s achieved 100%. This is the reason why it was immediately needed to use Graphic Processing Units called GPU’s which offer high level images processing. After GPU superscalar processor was integrated and done functional via module NVENC of FFEMPEG Program, number of channels transcoded simultaneously was tremendous increased (more than 100 channels). The aim of this paper is to real implement GPU superscalar processors in IPTV Cloud Networks by achieving improvement of performance to more than 60%. Keywords - GPU superscalar processor, Performance Improvement, NVENC, CUDA --------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 01 -05-2017 Date of acceptance: 19-08-2017 --------------------------------------------------------------------------------------------------------------------------------------- I. -
Computer Hardware Architecture Lecture 4
Computer Hardware Architecture Lecture 4 Manfred Liebmann Technische Universit¨atM¨unchen Chair of Optimal Control Center for Mathematical Sciences, M17 [email protected] November 10, 2015 Manfred Liebmann November 10, 2015 Reading List • Pacheco - An Introduction to Parallel Programming (Chapter 1 - 2) { Introduction to computer hardware architecture from the parallel programming angle • Hennessy-Patterson - Computer Architecture - A Quantitative Approach { Reference book for computer hardware architecture All books are available on the Moodle platform! Computer Hardware Architecture 1 Manfred Liebmann November 10, 2015 UMA Architecture Figure 1: A uniform memory access (UMA) multicore system Access times to main memory is the same for all cores in the system! Computer Hardware Architecture 2 Manfred Liebmann November 10, 2015 NUMA Architecture Figure 2: A nonuniform memory access (UMA) multicore system Access times to main memory differs form core to core depending on the proximity of the main memory. This architecture is often used in dual and quad socket servers, due to improved memory bandwidth. Computer Hardware Architecture 3 Manfred Liebmann November 10, 2015 Cache Coherence Figure 3: A shared memory system with two cores and two caches What happens if the same data element z1 is manipulated in two different caches? The hardware enforces cache coherence, i.e. consistency between the caches. Expensive! Computer Hardware Architecture 4 Manfred Liebmann November 10, 2015 False Sharing The cache coherence protocol works on the granularity of a cache line. If two threads manipulate different element within a single cache line, the cache coherency protocol is activated to ensure consistency, even if every thread is only manipulating its own data. -
Superscalar Fall 2020
CS232 Superscalar Fall 2020 Superscalar What is superscalar - A superscalar processor has more than one set of functional units and executes multiple independent instructions during a clock cycle by simultaneously dispatching multiple instructions to different functional units in the processor. - You can think of a superscalar processor as there are more than one washer, dryer, and person who can fold. So, it allows more throughput. - The order of instruction execution is usually assisted by the compiler. The hardware and the compiler assure that parallel execution does not violate the intent of the program. - Example: • Ordinary pipeline: four stages (Fetch, Decode, Execute, Write back), one clock cycle per stage. Executing 6 instructions take 9 clock cycles. I0: F D E W I1: F D E W I2: F D E W I3: F D E W I4: F D E W I5: F D E W cc: 1 2 3 4 5 6 7 8 9 • 2-degree superscalar: attempts to process 2 instructions simultaneously. Executing 6 instructions take 6 clock cycles. I0: F D E W I1: F D E W I2: F D E W I3: F D E W I4: F D E W I5: F D E W cc: 1 2 3 4 5 6 Limitations of Superscalar - The above example assumes that the instructions are independent of each other. So, it’s easily to push them into the pipeline and superscalar. However, instructions are usually relevant to each other. Just like the hazards in pipeline, superscalar has limitations too. - There are several fundamental limitations the system must cope, which are true data dependency, procedural dependency, resource conflict, output dependency, and anti- dependency. -
The Multiscalar Architecture
THE MULTISCALAR ARCHITECTURE by MANOJ FRANKLIN A thesis submitted in partial ful®llment of the requirements for the degree of DOCTOR OF PHILOSOPHY (Computer Sciences) at the UNIVERSITY OF WISCONSIN Ð MADISON 1993 THE MULTISCALAR ARCHITECTURE Manoj Franklin Under the supervision of Associate Professor Gurindar S. Sohi at the University of Wisconsin-Madison ABSTRACT The centerpiece of this thesis is a new processing paradigm for exploiting instruction level parallelism. This paradigm, called the multiscalar paradigm, splits the program into many smaller tasks, and exploits ®ne-grain parallelism by executing multiple, possibly (control and/or data) depen- dent tasks in parallel using multiple processing elements. Splitting the instruction stream at statically determined boundaries allows the compiler to pass substantial information about the tasks to the hardware. The processing paradigm can be viewed as extensions of the superscalar and multiprocess- ing paradigms, and shares a number of properties of the sequential processing model and the data¯ow processing model. The multiscalar paradigm is easily realizable, and we describe an implementation of the multis- calar paradigm, called the multiscalar processor. The central idea here is to connect multiple sequen- tial processors, in a decoupled and decentralized manner, to achieve overall multiple issue. The mul- tiscalar processor supports speculative execution, allows arbitrary dynamic code motion (facilitated by an ef®cient hardware memory disambiguation mechanism), exploits communication localities, and does all of these with hardware that is fairly straightforward to build. Other desirable aspects of the implementation include decentralization of the critical resources, absence of wide associative searches, and absence of wide interconnection/data paths. -
Trends in Processor Architecture
A. González Trends in Processor Architecture Trends in Processor Architecture Antonio González Universitat Politècnica de Catalunya, Barcelona, Spain 1. Past Trends Processors have undergone a tremendous evolution throughout their history. A key milestone in this evolution was the introduction of the microprocessor, term that refers to a processor that is implemented in a single chip. The first microprocessor was introduced by Intel under the name of Intel 4004 in 1971. It contained about 2,300 transistors, was clocked at 740 KHz and delivered 92,000 instructions per second while dissipating around 0.5 watts. Since then, practically every year we have witnessed the launch of a new microprocessor, delivering significant performance improvements over previous ones. Some studies have estimated this growth to be exponential, in the order of about 50% per year, which results in a cumulative growth of over three orders of magnitude in a time span of two decades [12]. These improvements have been fueled by advances in the manufacturing process and innovations in processor architecture. According to several studies [4][6], both aspects contributed in a similar amount to the global gains. The manufacturing process technology has tried to follow the scaling recipe laid down by Robert N. Dennard in the early 1970s [7]. The basics of this technology scaling consists of reducing transistor dimensions by a factor of 30% every generation (typically 2 years) while keeping electric fields constant. The 30% scaling in the dimensions results in doubling the transistor density (doubling transistor density every two years was predicted in 1975 by Gordon Moore and is normally referred to as Moore’s Law [21][22]). -
Intro Evolution of Superscalar Processor
Superscalar Processors Superscalar Processors vs. VLIW • 7.1 Introduction • 7.2 Parallel decoding • 7.3 Superscalar instruction issue • 7.4 Shelving • 7.5 Register renaming • 7.6 Parallel execution • 7.7 Preserving the sequential consistency of instruction execution • 7.8 Preserving the sequential consistency of exception processing • 7.9 Implementation of superscalar CISC processors using a superscalar RISC core • 7.10 Case studies of superscalar processors TECH Computer Science CH01 Superscalar Processor: Intro Emergence and spread of superscalar processors • Parallel Issue • Parallel Execution • {Hardware} Dynamic Instruction Scheduling • Currently the predominant class of processors 4Pentium 4PowerPC 4UltraSparc 4AMD K5- 4HP PA7100- 4DEC α Evolution of superscalar processor Specific tasks of superscalar processing Parallel decoding {and Dependencies check} Decoding and Pre-decoding • What need to be done • Superscalar processors tend to use 2 and sometimes even 3 or more pipeline cycles for decoding and issuing instructions • >> Pre-decoding: 4shifts a part of the decode task up into loading phase 4resulting of pre-decoding f the instruction class f the type of resources required for the execution f in some processor (e.g. UltraSparc), branch target addresses calculation as well 4the results are stored by attaching 4-7 bits • + shortens the overall cycle time or reduces the number of cycles needed The principle of perdecoding Number of perdecode bits used Specific tasks of superscalar processing: Issue 7.3 Superscalar instruction issue • How and when to send the instruction(s) to EU(s) Instruction issue policies of superscalar processors: Issue policies ---Performance, tread-----Æ Issue rate {How many instructions/cycle} Issue policies: Handing Issue Blockages • CISC about 2 • RISC: Issue stopped by True dependency Issue order of instructions • True dependency Æ (Blocked: need to wait) Aligned vs. -
Parallel Architectures MICHAEL J
Parallel Architectures MICHAEL J. FLYNN AND KEVIN W. RUDD Stanford University ^[email protected]&; ^[email protected]& PARALLEL ARCHITECTURES currently performing different phases of processing an instruction. This does not Parallel or concurrent operation has achieve concurrency of execution (with many different forms within a computer system. Using a model based on the multiple actions being taken on objects) different streams used in the computa- but does achieve a concurrency of pro- tion process, we represent some of the cessing—an improvement in efficiency different kinds of parallelism available. upon which almost all processors de- A stream is a sequence of objects such pend today. as data, or of actions such as instruc- Techniques that exploit concurrency tions. Each stream is independent of all of execution, often called instruction- other streams, and each element of a level parallelism (ILP), are also com- stream can consist of one or more ob- mon. Two architectures that exploit ILP jects or actions. We thus have four com- are superscalar and VLIW (very long binations that describe most familiar parallel architectures: instruction word). These techniques schedule different operations to execute (1) SISD: single instruction, single data concurrently based on analyzing the de- stream. This is the traditional uni- pendencies between the operations processor [Figure 1(a)]. within the instruction stream—dynami- (2) SIMD: single instruction, multiple cally at run time in a superscalar pro- data stream. This includes vector cessor and statically at compile time in processors as well as massively par- a VLIW processor. Both ILP approaches allel processors [Figure 1(b)]. -
ESC-470: ARM 9 Instruction Set Architecture with Performance
ARM 9 Instruction Set Architecture Introduction with Performance Perspective Joe-Ming Cheng, Ph.D. ARM-family processors are positioned among the leaders in key embedded applications. Many presentations and short lectures have already addressed the ARM’s applications and capabilities. In this introduction, we intend to discuss the ARM’s instruction set uniqueness from the performance prospective. This introduction is also trying to follow the approaches established by two outstanding textbooks of David Patterson and John Hennessey [PetHen00] [HenPet02]. 1.0 ARM Instruction Set Architecture Processor instruction set architecture (ISA) choices have evolved from accumulator, stack, register-to- memory, to register-register (load-store) organization. ARM 9 ISA is a load-store machine. ARM 9 ISA takes advantage of its smaller set of registers (16 vs. many 32-register processors) to incorporate more direct controls and achieve high encoding density. ARM’s load or store multiple register instruction, for example , allows enlisting of all possible registers and conditional execution in one instruction. The Thumb mode instruction set is another exa mple of how ARM ISA facilitates higher encode density. Rather than compressing the code, Thumb -mode instructions are two 16-bit instructions packed in a 32-bit ARM-mode instruction space. The Thumb -mode instructions are a subset of ARM instructions. When executing in Thumb mode, a single 32-bit instruction fetch cycle effectively brings in two instructions. Thumb code reduces access bandwidth, code size, and improves instruction cache hit rate. Another way ARM achieves cycle time reduction is by using Harvard architecture. The architecture facilitates independent data and instruction buses. -
RISC-V Geneology
RISC-V Geneology Tony Chen David A. Patterson Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2016-6 http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-6.html January 24, 2016 Copyright © 2016, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Introduction RISC-V is an open instruction set designed along RISC principles developed originally at UC Berkeley1 and is now set to become an open industry standard under the governance of the RISC-V Foundation (www.riscv.org). Since the instruction set architecture (ISA) is unrestricted, organizations can share implementations as well as open source compilers and operating systems. Designed for use in custom systems on a chip, RISC-V consists of a base set of instructions called RV32I along with optional extensions for multiply and divide (RV32M), atomic operations (RV32A), single-precision floating point (RV32F), and double-precision floating point (RV32D). The base and these four extensions are collectively called RV32G. This report discusses the historical precedents of RV32G. We look at 18 prior instruction set architectures, chosen primarily from earlier UC Berkeley RISC architectures and major proprietary RISC instruction sets. Among the 122 instructions in RV32G: ● 6 instructions do not have precedents among the selected instruction sets, ● 98 instructions of the 116 with precedents appear in at least three different instruction sets. -
A CAD Tool for Synthesizing Optimized Variants of Altera's Nios II Soft-Core Processor
A CAD Tool for Synthesizing Optimized Variants of Altera's Nios II Soft-Core Processor By Omar Al Rayahi A Thesis Submitted to the Faculty of Graduate Studies through Electrical and Computer Engineering in Partial Fulfillment of the Requirements for the Degree of Master of Applied Science at the University of Windsor Windsor, Ontario, Canada 2008 Library and Bibliotheque et 1*1 Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-47050-3 Our file Notre reference ISBN: 978-0-494-47050-3 NOTICE: AVIS: The author has granted a non L'auteur a accorde une licence non exclusive exclusive license allowing Library permettant a la Bibliotheque et Archives and Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Plntemet, prefer, telecommunication or on the Internet, distribuer et vendre des theses partout dans loan, distribute and sell theses le monde, a des fins commerciales ou autres, worldwide, for commercial or non sur support microforme, papier, electronique commercial purposes, in microform, et/ou autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in et des droits moraux qui protege cette these. this thesis. Neither the thesis Ni la these ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent etre imprimes ou autrement may be printed or otherwise reproduits sans son autorisation. -
Small Soft Core up Inventory ©2019 James Brakefield Opencore and Other Soft Core Processors Reverse-U16 A.T
tool pip _uP_all_soft opencores or style / data inst repor com LUTs blk F tool MIPS clks/ KIPS ven src #src fltg max max byte adr # start last secondary web status author FPGA top file chai e note worthy comments doc SOC date LUT? # inst # folder prmary link clone size size ter ents ALUT mults ram max ver /inst inst /LUT dor code files pt Hav'd dat inst adrs mod reg year revis link n len Small soft core uP Inventory ©2019 James Brakefield Opencore and other soft core processors reverse-u16 https://github.com/programmerby/ReVerSE-U16stable A.T. Z80 8 8 cylcone-4 James Brakefield11224 4 60 ## 14.7 0.33 4.0 X Y vhdl 29 zxpoly Y yes N N 64K 64K Y 2015 SOC project using T80, HDMI generatorretro Z80 based on T80 by Daniel Wallner copyblaze https://opencores.org/project,copyblazestable Abdallah ElIbrahimi picoBlaze 8 18 kintex-7-3 James Brakefieldmissing block622 ROM6 217 ## 14.7 0.33 2.0 57.5 IX vhdl 16 cp_copyblazeY asm N 256 2K Y 2011 2016 wishbone extras sap https://opencores.org/project,sapstable Ahmed Shahein accum 8 8 kintex-7-3 James Brakefieldno LUT RAM48 or block6 RAM 200 ## 14.7 0.10 4.0 104.2 X vhdl 15 mp_struct N 16 16 Y 5 2012 2017 https://shirishkoirala.blogspot.com/2017/01/sap-1simple-as-possible-1-computer.htmlSimple as Possible Computer from Malvinohttps://www.youtube.com/watch?v=prpyEFxZCMw & Brown "Digital computer electronics" blue https://opencores.org/project,bluestable Al Williams accum 16 16 spartan-3-5 James Brakefieldremoved clock1025 constraint4 63 ## 14.7 0.67 1.0 41.1 X verilog 16 topbox web N 4K 4K N 16 2 2009 -
Design of the RISC-V Instruction Set Architecture
Design of the RISC-V Instruction Set Architecture Andrew Waterman Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2016-1 http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-1.html January 3, 2016 Copyright © 2016, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Design of the RISC-V Instruction Set Architecture by Andrew Shell Waterman A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the Graduate Division of the University of California, Berkeley Committee in charge: Professor David Patterson, Chair Professor Krste Asanovi´c Associate Professor Per-Olof Persson Spring 2016 Design of the RISC-V Instruction Set Architecture Copyright 2016 by Andrew Shell Waterman 1 Abstract Design of the RISC-V Instruction Set Architecture by Andrew Shell Waterman Doctor of Philosophy in Computer Science University of California, Berkeley Professor David Patterson, Chair The hardware-software interface, embodied in the instruction set architecture (ISA), is arguably the most important interface in a computer system. Yet, in contrast to nearly all other interfaces in a modern computer system, all commercially popular ISAs are proprietary.