Emips, a Dynamically Extensible Processor

Total Page:16

File Type:pdf, Size:1020Kb

Emips, a Dynamically Extensible Processor Automatic Generation of Interrupt-Aware Hardware Accelerators with the M2V Compiler Abilash Sekar, Alessandro Forin Microsoft Research August 2008 Technical Report MSR-TR-2008-110 Microsoft Research Microsoft Corporation One Microsoft Way Redmond, WA 98052 - 2 - Automatic Generation of Interrupt-Aware Hardware Accelerators with the M2V Compiler Abilash Sekar, Alessandro Forin Microsoft Research Extensible processors take advantage of the fact that a Abstract small amount of code takes the majority of execution time in a typical program. The code that executes most often is The MIPS-to-Verilog (M2V) compiler and the Basic a candidate for hardware acceleration. The code is Block Tools (BBTools) can automatically generate a identified by a special instruction that will initiate the hardware accelerator for selected blocks of machine code accelerator. in an application. The compiler translates blocks of MIPS *.BBW BB Tools Extension machine code into a hardware design captured in Verilog Basic Block File (an "Extension"). The BBTools patch the application *.EXE M2V *.V Compiled (MIPS to Synthesizable binary by inserting the extension instruction that triggers Binary Verilog Verilog the accelerator. The original code is preserved, so that Executable Compiler) execution can fall back to software when necessary. GIANO *.EXE Simulator Patched Binary This work extends the M2V compiler with support for memory load and store instructions, and for interrupts. Figure 1: The eMIPS Tool Chain to automate the We use a transactional model to handle interrupts and/or generation of hardware accelerators. traps due to TLB misses in the Extension. We implemented Selection of the best code to accelerate is an active and tested the interrupt support mechanism using a 64-bit area of research. The eMIPS tool-chain, shown in Figure division basic block, with added instructions for memory 1, restricts the code selection problem to the set of basic loads off the stack pointer. blocks in the application. Using the strict definition in [1], We also added the feature of allowing the BBTools to the basic block is a directed acyclic graph (DAG). A automatically create the best encoding for an extension DAG is a set of machine instructions that do not contain instruction. The tool now evaluates which pair of roots in branches and are branched-to only for the very first the dependency graph leads to the shortest execution instruction. The best candidate blocks are currently cycle time for the Extension. With this addition, the selected by executing the application using the Giano full- process of creating Extensions for the eMIPS processor system simulator [21], in concert with the data obtained can now be fully automated and applied to practical via static analysis of the application binary. The BBTools applications, where loads and stores inside the Extension select the basic blocks to accelerate and patch the binary are of paramount importance. image with the special instructions for the accelerator. The M2V compiler [16] automatically generates the 1 Introduction design for the hardware accelerator, which is then synthesized using the Xilinx tools for the ML40x boards. Extensible processors have a simple RISC pipeline The accelerator can be statically loaded when eMIPS and the ability to augment the Instruction Set Architecture is reset or it can be dynamically loaded when an (ISA) with custom instructions. The ISA can be application is loaded using partial reconfiguration of the augmented statically, at tape-out, or it can be augmented FPGA. By dynamically loading and unloading dynamically when applications are loaded. Extensible accelerators, the area of the programmable hardware can processors differ from other accelerators in their tight be used more efficiently. integration with the basic data path, which leads to In previous versions of eMIPS, the accelerator blocks minimal latencies and therefore greater flexibility. could be specified and given to a hardware designer to Examples of dynamically extensible processors include hand design the accelerator. While this can lead to an eMIPS [6] and Stretch [13]. Tensilica’s Xtensa [14] is an efficient implementation, manual designs do not scale well example of a statically extensible processor. - 3 - as dynamically extensible processors are more widely The third limitation addresses the task of used and the hardware becomes more complex. To automatically choosing an instruction encoding for the effectively utilize dynamically extensible processors, new extension instruction. We observed that the selection different parts of an application can be accelerated using of which registers or constants to encode in the instruction different Extensions, which can be loaded at appropriate can have an effect on the overall execution time. These times. The use of the tool chain along with M2V can values are available early in the execution pipeline. It is expand the use of hardware acceleration and completely therefore important to select those that allow the most automate the process of generating hardware accelerators work to proceed before stalling on a dependency. Our for a variety of basic blocks in an application. algorithm uses two parameters in deciding which two The work described herein addresses three limitations register numbers to encode – fan-out and depth of the root in the tool chain that prevented the M2V tool chain from register read nodes. It selects the pair of registers with the being usable in but a few practical cases. The first maximum combined fan-out and depth. limitation was the lack of support for load and store The remainder of this document is structured as operations, and more generally for variable-cost follows. Section 2 discusses related work. Section 3 gives operations. M2V was previously only able to cope with an overview of the eMIPS hardware platform. Section 4 MIPS instructions that took zero or one cycle. We added discusses the automatic encoding of the extension support for all the instructions that took a fixed number of instruction by the BBTools. Section 5 defines the support cycles, accounting for the cost in the generation of the for memory operations in the M2V compiler. Section 6 schedule. Then we added support for the instructions that discusses the model and implementation for handling have variable costs, prime and foremost loads and stores. interrupts in the Extension. Section 7 explains the M2V We were able to find a way to preserve the overall generated hardware in more detail. Section 8 compares structure of the compiler, while dealing with the variable the synthesis reports obtained for Extensions generated costs. The dependency graph still leads to a state machine with and without the transactional model enabled. Section that controls the overall execution. The transitions are now 9 discusses the experimental results, and Section 10 defined not only by the clock, but also by the signals that concludes the report. Appendix I contains the BBW file indicate completion of the variable-cost operations. for the example basic block. Appendix II contains The second limitation concerns the inability of the synthesis reports for the Extension generated by the M2V M2V compiler to generate logic for handling interrupts compiler. Appendix III contains the Verilog output from within an Extension. External interrupts could only M2V, with the transactional model enabled and interrupt happen before or after the extension instruction, never support. Appendix IV shows an automated visualization inside it. This assumption is invalid in the presence of of the dependency graphs from M2V. TLB misses due to loads and stores. Furthermore, the previous tool required that an Extension never encounter 2 Related Work errors, such as arithmetic overflows or unaligned addresses. For a real-time system, it is important to Work on extensible processors can be divided in respond to interrupts in a timely and predictable manner. several ways. One avenue of exploration is to define the Even in a general-purpose OS it is unacceptable to allow a underlying hardware. Chimaera [7] and GARP [8] are user process to ignore interrupts and lock the machine. To two examples of extensible hardware from the late 1990’s. address the interrupt limitation, we used the concept of Commercial FPGA manufacturers today all provide transactions in dealing with the write-backs to the register examples of soft-cores, microprocessor designs that the file and the stores to memory. The overall execution of the customer can modify and extend for their application [15, Extension is subdivided in sets that execute “atomically”. 3, 13]. M2V uses the eMIPS processor [6] as its Interruptions of any sort are accepted at the transaction underlying hardware platform. eMIPS is the first design boundaries. On interruption, the write-back machine that is secure for general purpose multi-user loads, and the cancels all write-backs from future transactions, completes set of potential applications is therefore more open-ended the write-backs for the current one, and then relinquishes than those found in the typical embedded system alone. control back to the data-path in a limited amount of time. A common approach to generate code for an The restart-address is set to the point in the original basic extensible processor is to modify an existing C compiler. block that corresponds to the current write-back state. It is Tensilica [14] automatically regenerates a full GNU therefore mandatory that extension instructions are simply compilation system given the RTL of the new instruction. inserted in the original image, and that they do not replace Ienne et al. [4] use the SUIF compiler. M2V accepts as the original basic block. input binary machine code rather than source code. There are trade-offs between accelerating from source code in a - 4 - high-level language or from binaries. One of the major the basic block, so that it can identify repeating basic advantages when accelerating from binaries is that any blocks in the binary. application can be accelerated, even applications where the source code is controlled by an outside party and not 3 eMIPS Hardware Overview available to the system developer.
Recommended publications
  • Design and VHDL Implementation of an Application-Specific Instruction Set Processor
    Design and VHDL Implementation of an Application-Specific Instruction Set Processor Lauri Isola School of Electrical Engineering Thesis submitted for examination for the degree of Master of Science in Technology. Espoo 19.12.2019 Supervisor Prof. Jussi Ryynänen Advisor D.Sc. (Tech.) Marko Kosunen Copyright © 2019 Lauri Isola Aalto University, P.O. BOX 11000, 00076 AALTO www.aalto.fi Abstract of the master’s thesis Author Lauri Isola Title Design and VHDL Implementation of an Application-Specific Instruction Set Processor Degree programme Computer, Communication and Information Sciences Major Signal, Speech and Language Processing Code of major ELEC3031 Supervisor Prof. Jussi Ryynänen Advisor D.Sc. (Tech.) Marko Kosunen Date 19.12.2019 Number of pages 66+45 Language English Abstract Open source processors are becoming more popular. They are a cost-effective option in hardware designs, because using the processor does not require an expensive license. However, a limited number of open source processors are still available. This is especially true for Application-Specific Instruction Set Processors (ASIPs). In this work, an ASIP processor was designed and implemented in VHDL hardware description language. The design was based on goals that make the processor easily customizable, and to have a low resource consumption in a System- on-Chip (SoC) design. Finally, the processor was implemented on an FPGA circuit, where it was tested with a specially designed VGA graphics controller. Necessary software tools, such as an assembler were also implemented for the processor. The assembler was used to write comprehensive test programs for testing and verifying the functionality of the processor. This work also examined some future upgrades of the designed processor.
    [Show full text]
  • Comparative Architectures
    Comparative Architectures CST Part II, 16 lectures Lent Term 2006 David Greaves [email protected] Slides Lectures 1-13 (C) 2006 IAP + DJG Course Outline 1. Comparing Implementations • Developments fabrication technology • Cost, power, performance, compatibility • Benchmarking 2. Instruction Set Architecture (ISA) • Classic CISC and RISC traits • ISA evolution 3. Microarchitecture • Pipelining • Super-scalar { static & out-of-order • Multi-threading • Effects of ISA on µarchitecture and vice versa 4. Memory System Architecture • Memory Hierarchy 5. Multi-processor systems • Cache coherent and message passing Understanding design tradeoffs 2 Reading material • OHP slides, articles • Recommended Book: John Hennessy & David Patterson, Computer Architecture: a Quantitative Approach (3rd ed.) 2002 Morgan Kaufmann • MIT Open Courseware: 6.823 Computer System Architecture, by Krste Asanovic • The Web http://bwrc.eecs.berkeley.edu/CIC/ http://www.chip-architect.com/ http://www.geek.com/procspec/procspec.htm http://www.realworldtech.com/ http://www.anandtech.com/ http://www.arstechnica.com/ http://open.specbench.org/ • comp.arch News Group 3 Further Reading and Reference • M Johnson Superscalar microprocessor design 1991 Prentice-Hall • P Markstein IA-64 and Elementary Functions 2000 Prentice-Hall • A Tannenbaum, Structured Computer Organization (2nd ed.) 1990 Prentice-Hall • A Someren & C Atack, The ARM RISC Chip, 1994 Addison-Wesley • R Sites, Alpha Architecture Reference Manual, 1992 Digital Press • G Kane & J Heinrich, MIPS RISC Architecture
    [Show full text]
  • CS152: Computer Systems Architecture Pipelining
    CS152: Computer Systems Architecture Pipelining Sang-Woo Jun Winter 2021 Large amount of material adapted from MIT 6.004, “Computation Structures”, Morgan Kaufmann “Computer Organization and Design: The Hardware/Software Interface: RISC-V Edition”, and CS 152 Slides by Isaac Scherson Eight great ideas ❑ Design for Moore’s Law ❑ Use abstraction to simplify design ❑ Make the common case fast ❑ Performance via parallelism ❑ Performance via pipelining ❑ Performance via prediction ❑ Hierarchy of memories ❑ Dependability via redundancy But before we start… Performance Measures ❑ Two metrics when designing a system 1. Latency: The delay from when an input enters the system until its associated output is produced 2. Throughput: The rate at which inputs or outputs are processed ❑ The metric to prioritize depends on the application o Embedded system for airbag deployment? Latency o General-purpose processor? Throughput Performance of Combinational Circuits ❑ For combinational logic o latency = tPD o throughput = 1/t F and G not doing work! PD Just holding output data X F(X) X Y G(X) H(X) Is this an efficient way of using hardware? Source: MIT 6.004 2019 L12 Pipelined Circuits ❑ Pipelining by adding registers to hold F and G’s output o Now F & G can be working on input Xi+1 while H is performing computation on Xi o A 2-stage pipeline! o For input X during clock cycle j, corresponding output is emitted during clock j+2. Assuming ideal registers Assuming latencies of 15, 20, 25… 15 Y F(X) G(X) 20 H(X) 25 Source: MIT 6.004 2019 L12 Pipelined Circuits 20+25=45 25+25=50 Latency Throughput Unpipelined 45 1/45 2-stage pipelined 50 (Worse!) 1/25 (Better!) Source: MIT 6.004 2019 L12 Pipeline conventions ❑ Definition: o A well-formed K-Stage Pipeline (“K-pipeline”) is an acyclic circuit having exactly K registers on every path from an input to an output.
    [Show full text]
  • Quantum Chemical Computational Methods Have Proved to Be An
    34671 K. Immanuvel Arokia James et al./ Elixir Comp. Sci. & Engg. 85 (2015) 34671-34676 Available online at www.elixirpublishers.com (Elixir International Journal) Computer Science and Engineering Elixir Comp. Sci. & Engg. 85 (2015) 34671-34676 Outerloop pipelining in FFT using single dimension software pipelining K. Immanuvel Arokia James1 and M. J. Joyce Kiruba2 1Department of EEE VEL Tech Multi Tech Dr. RR Dr. SR Engg College, Chennai, India. 2Department of ECE, Dr. MGR University, Chennai, India. ARTICLE INFO ABSTRACT Article history: The aim of the paper is to produce faster results when pipelining above the inner most loop. Received: 19 May 2012; The concept of outerloop pipelining is tested here with Fast Fourier Transform. Reduction Received in revised form: in the number of cycles spent flushing and filling the pipeline and the potential for data reuse 22 August 2015; is another advantage in the outerloop pipelining. In this work we extend and adapt the Accepted: 29 August 2015; existing SSP approach to better suit the generation of schedules for hardware, specifically FPGAs. We also introduce a search scheme to find the shortest schedule available within the Keywords pipelining framework to maximize the gains in pipelining above the innermost loop. The FFT, hardware compilers apply loop pipelining to increase the parallelism achieved, but Pipelining, VHDL, pipelining is restricted to the only innermost level in nested loop. In this work we extend and Nested loop, adapt an existing outer loop pipelining approach known as Single Dimension Software FPGA, Pipelining to generate schedules for FPGA hardware coprocessors. Each loop level in nine Integer Linear Programming (ILP).
    [Show full text]
  • Design and Implementation of a Multithreaded Associative Simd Processor
    DESIGN AND IMPLEMENTATION OF A MULTITHREADED ASSOCIATIVE SIMD PROCESSOR A dissertation submitted to Kent State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy by Kevin Schaffer December, 2011 Dissertation written by Kevin Schaffer B.S., Kent State University, 2001 M.S., Kent State University, 2003 Ph.D., Kent State University, 2011 Approved by Robert A. Walker, Chair, Doctoral Dissertation Committee Johnnie W. Baker, Members, Doctoral Dissertation Committee Kenneth E. Batcher, Eugene C. Gartland, Accepted by John R. D. Stalvey, Administrator, Department of Computer Science Timothy Moerland, Dean, College of Arts and Sciences ii TABLE OF CONTENTS LIST OF FIGURES ......................................................................................................... viii LIST OF TABLES ............................................................................................................. xi CHAPTER 1 INTRODUCTION ........................................................................................ 1 1.1. Architectural Trends .............................................................................................. 1 1.1.1. Wide-Issue Superscalar Processors............................................................... 2 1.1.2. Chip Multiprocessors (CMPs) ...................................................................... 2 1.2. An Alternative Approach: SIMD ........................................................................... 3 1.3. MTASC Processor ................................................................................................
    [Show full text]
  • Notes-Cso-Unit-5
    Unit-05/Lecture-01 Pipeline Processing In computing, a pipeline is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion; in that case, some amount of buffer storage is often inserted between elements. Computer-related pipelines include: Instruction pipelines, such as the classic RISC pipeline, which are used in central processing units (CPUs) to allow overlapping execution of multiple instructions with the same circuitry. The circuitry is usually divided up into stages, including instruction decoding, arithmetic, and register fetching stages, wherein each stage processes one instruction at a time. Graphics pipelines, found in most graphics processing units (GPUs), which consist of multiple arithmetic units, or complete CPUs, that implement the various stages of common rendering operations (perspective projection, window clipping, color and light calculation, rendering, etc.). Software pipelines, where commands can be written where the output of one operation is automatically fed to the next, following operation. The Unix system call pipe is a classic example of this concept, although other operating systems do support pipes as well. Pipelining is a natural concept in everyday life, e.g. on an assembly line. Consider the assembly of a car: assume that certain steps in the assembly line are to install the engine, install the hood, and install the wheels (in that order, with arbitrary interstitial steps). A car on the assembly line can have only one of the three steps done at once.
    [Show full text]
  • Specifying, Verifying, and Translating Between Memory Consistency Models
    Specifying, Verifying, and Translating Between Memory Consistency Models Daniel Joseph Lustig A Dissertation Presented to the Faculty of Princeton University in Candidacy for the Degree of Doctor of Philosophy Recommended for Acceptance by the Department of Electrical Engineering Adviser: Professor Margaret Martonosi November 2015 © Copyright by Daniel Joseph Lustig, 2015. All rights reserved. Abstract Gone are the days when single-threaded performance was the primary metric of in- terest for a processor design. Driven by increasingly tight power constraints and by the slowing down of Moore's law and Dennard scaling, architects have turned to mul- ticore parallelism and architectural heterogeneity as a means to continue delivering increases in chip performance and power efficiency. Both approaches can deliver im- proved performance per watt characteristics at the expense of creating systems which are dramatically more complex to design and harder to program. In order to share data and coordinate their actions, the compute elements (e.g., CPU cores, GPU cores, accelerators) in modern processors communicate via shared virtual memory. In this model, regardless of the underlying physical reality, cores see the abstraction of a single unified address space shared with the other processing elements in the system. Communication through shared virtual memory takes place according to a memory consistency model|the set of rules and guarantees about the ordering and visibility of memory accesses issued by one processing element and observed by other processing elements. Unfortunately, in practice, hardware consis- tency model definitions frequently suffer from a lack of formalism, precision, and/or completeness, resulting in numerous situations in which the correct outcome(s) for a given scenario may be ambiguous or even simply undefined.
    [Show full text]
  • Jon Stokes Jon
    Inside the Machine the Inside A Look Inside the Silicon Heart of Modern Computing Architecture Computer and Microprocessors to Introduction Illustrated An Computers perform countless tasks ranging from the business critical to the recreational, but regardless of how differently they may look and behave, they’re all amazingly similar in basic function. Once you understand how the microprocessor—or central processing unit (CPU)— Includes discussion of: works, you’ll have a firm grasp of the fundamental concepts at the heart of all modern computing. • Parts of the computer and microprocessor • Programming fundamentals (arithmetic Inside the Machine, from the co-founder of the highly instructions, memory accesses, control respected Ars Technica website, explains how flow instructions, and data types) microprocessors operate—what they do and how • Intermediate and advanced microprocessor they do it. The book uses analogies, full-color concepts (branch prediction and speculative diagrams, and clear language to convey the ideas execution) that form the basis of modern computing. After • Intermediate and advanced computing discussing computers in the abstract, the book concepts (instruction set architectures, examines specific microprocessors from Intel, RISC and CISC, the memory hierarchy, and IBM, and Motorola, from the original models up encoding and decoding machine language through today’s leading processors. It contains the instructions) most comprehensive and up-to-date information • 64-bit computing vs. 32-bit computing available (online or in print) on Intel’s latest • Caching and performance processors: the Pentium M, Core, and Core 2 Duo. Inside the Machine also explains technology terms Inside the Machine is perfect for students of and concepts that readers often hear but may not science and engineering, IT and business fully understand, such as “pipelining,” “L1 cache,” professionals, and the growing community “main memory,” “superscalar processing,” and of hardware tinkerers who like to dig into the “out-of-order execution.” guts of their machines.
    [Show full text]
  • MIPS-To-Verilog, Hardware Compilation for the Emips Processor
    MIPS-to-Verilog, Hardware Compilation for the eMIPS Processor Karl Meier, Alessandro Forin Microsoft Research September 2007 Technical Report MSR-TR-2007-128 Microsoft Research Microsoft Corporation One Microsoft Way Redmond, WA 98052 - 2 - MIPS-to-Verilog, Hardware Compilation for the eMIPS Processor Karl Meier, Alessandro Forin Microsoft Research architecture (ISA) and without a FPU may suffer from Abstract poor performance. Extensible processors try to compromise between The MIPS-to-Verilog (M2V) compiler translates general purpose CPUs and minimal RISC blocks of MIPS machine code into a hardware design implementations. Extensible processors have a simple represented in Verilog. The design constitutes an RISC pipeline and the ability to augment the ISA with Extension for the eMIPS processor, a dynamically custom instructions. The ISA can be augmented extensible processor realized on the Virtex-4 XC4LX25 statically, at tape-out, or it can be augmented dynamically FPGA. The Extension interacts closely with the basic when applications are loaded. The eMIPS processor is an pipeline of the microprocessor and recognizes special example of a dynamically extensible processor. Extension Instructions, instructions that are not part of Extensible processors take advantage of the fact that a the basic MIPS ISA. Each instruction is semantically small amount of code takes the majority of execution time equivalent to one or more blocks of MIPS code. The purpose of the M2V compiler is to automate the process in a typical program. The code that executes most often is of creating Extensions for the specific purpose of a candidate for hardware acceleration. The code must be accelerating the execution of software programs.
    [Show full text]
  • DEPARTMENT of INFORMATICS Optimization of Small Matrix
    DEPARTMENT OF INFORMATICS TECHNISCHE UNIVERSITÄT MÜNCHEN Bachelor’s Thesis in Informatics Optimization of small matrix multiplication kernels on Arm Jonas Schreier DEPARTMENT OF INFORMATICS TECHNISCHE UNIVERSITÄT MÜNCHEN Bachelor’s Thesis in Informatics Optimization of small matrix multiplication kernels on Arm Optimierung von Multiplikationskernels für kleine Matritzen auf Arm Architekturen Author: Jonas Schreier Supervisor: Michael Bader Advisor: Lukas Krenz Submission Date: 15.03.2021 I confirm that this bachelor’s thesis in informatics is my own work and I have docu- mented all sources and material used. Munich, 15.03.2021 Jonas Schreier Acknowledgments I would like to thank: The Chair of Scientific Computing at TUM and Prof. Dr. Michael Bader for giving me the opportunity to start this project and my advisor Lukas Krenz for giving me guidance. Abstract Matrix multiplication is essential for many numerical applications. Thus, efficient multiplication kernels are necessary to reach optimal performance. Most efforts in this direction are targeted towards x86 architectures, but recent developments have shown promise when traditional x86 computing contexts are ported to Arm architectures. This work analyses different approaches of generating highly optimized kernels for small dense GEMM on Arm. Benchmarks of generated code are performed on ThunderX2 (NEON vector extension) and Fujitsu A64FX (Scalable Vector extension). While multiple possible solutions to the DGEMM problem on Arm exist, a general solution that performs best for all use cases could not be found. The largest deciding factor was the vector extension implemented by the respective target CPU. iv Contents Acknowledgments iii Abstract iv 1 Introduction 1 1.1 Motivation . .1 1.2 SeisSol .
    [Show full text]
  • CS3350B Computer Organization Chapter 3: CPU Control & Datapath
    CS3350B Computer Organization Chapter 3: CPU Control & Datapath Part 1: Introduction to MIPS Alex Brandt Department of Computer Science University of Western Ontario, Canada Thursday February 14, 2019 Alex Brandt Chapter 3: CPU Control & Datapath , Part 1: Intro to MIPS Thursday February 14, 2019 1 / 44 Outline 1 Overview 2 MIPS Assemebly 3 Instruction Fetch & Instruction Decode 4 MIPS Instruction Formats 5 Aside: Program Memory Space Alex Brandt Chapter 3: CPU Control & Datapath , Part 1: Intro to MIPS Thursday February 14, 2019 2 / 44 Layers of Abstraction We will put together the combinational circuits and state circuits to see how a CPU actually works. How does data flow through the CPU? How are the path and circuits (MUX, ALU, registers) controlled? Alex Brandt Chapter 3: CPU Control & Datapath , Part 1: Intro to MIPS Thursday February 14, 2019 3 / 44 Preview: MIPS Datapath Alex Brandt Chapter 3: CPU Control & Datapath , Part 1: Intro to MIPS Thursday February 14, 2019 4 / 44 MIPS ISA MIPS ISA: Microprocessor without Interlocked Pipelined Stages. ë ISA: The language of the computer. ë Microprocessor: a CPU. ë Interlocking: To come in chapter 4. ë Pipelined Stages: The data path is broken into a ubiquitous 5-stage pipeline (also chapter 4). MIPS is a RISC ISA. RISC: Reduced Instruction Set Computer. ë Provided instructions are simple, datapath is simple. Contrast with CISC: Complex Instruction Set Computer. ë Instructions can be very “meta”, each performing many lower-level instructions. Alex Brandt Chapter 3: CPU Control & Datapath
    [Show full text]
  • An Open Characterizing Platform for Integrated Circuits Morgan Bourrée, Florent Bruguier, Lyonel Barthe, Pascal Benoit, Philippe Maurine, Lionel Torres
    SECNUM: an Open Characterizing Platform for Integrated Circuits Morgan Bourrée, Florent Bruguier, Lyonel Barthe, Pascal Benoit, Philippe Maurine, Lionel Torres To cite this version: Morgan Bourrée, Florent Bruguier, Lyonel Barthe, Pascal Benoit, Philippe Maurine, et al.. SECNUM: an Open Characterizing Platform for Integrated Circuits. European Workshop on Microelectronics Education (EWME), May 2012, Grenoble, France. hal-01139176 HAL Id: hal-01139176 https://hal.archives-ouvertes.fr/hal-01139176 Submitted on 3 Apr 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License EWME, 9-11 May, 2012 - Grenoble, France SECNUM: an Open Characterizing Platform for Integrated Circuits Morgan Bourrée, Florent Bruguier, Lyonel Barthe, Pascal Benoit, Philippe Maurine, Lionel Torres LIRMM – UM2 - CNRS e-mail: {firstname.lastname}@lirmm.fr Abstract: Our lab equipment is fully automated with scripts and is Nowadays, digital systems are becoming the main information described in Fig.1. It allows both power and electromagnetic support. This evolution implies a growing interest for the analyses. It is composed of a high frequency near-field probe domain of cryptology regarding the conception of these [3] positioned above the chip (Fig.2), connected to a Low systems.
    [Show full text]