Embedded Systems Course Using Altera FPGA Subramaniam Ganesan, Oakland University, [email protected]
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Co-Simulation Between Cλash and Traditional Hdls
MASTER THESIS CO-SIMULATION BETWEEN CλASH AND TRADITIONAL HDLS Author: John Verheij Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) Computer Architecture for Embedded Systems (CAES) Exam committee: Dr. Ir. C.P.R. Baaij Dr. Ir. J. Kuper Dr. Ir. J.F. Broenink Ir. E. Molenkamp August 19, 2016 Abstract CλaSH is a functional hardware description language (HDL) developed at the CAES group of the University of Twente. CλaSH borrows both the syntax and semantics from the general-purpose functional programming language Haskell, meaning that circuit de- signers can define their circuits with regular Haskell syntax. CλaSH contains a compiler for compiling circuits to traditional hardware description languages, like VHDL, Verilog, and SystemVerilog. Currently, compiling to traditional HDLs is one-way, meaning that CλaSH has no simulation options with the traditional HDLs. Co-simulation could be used to simulate designs which are defined in multiple lan- guages. With co-simulation it should be possible to use CλaSH as a verification language (test-bench) for traditional HDLs. Furthermore, circuits defined in traditional HDLs, can be used and simulated within CλaSH. In this thesis, research is done on the co-simulation of CλaSH and traditional HDLs. Traditional hardware description languages are standardized and include an interface to communicate with foreign languages. This interface can be used to include foreign func- tions, or to make verification and co-simulation possible. Because CλaSH also has possibilities to communicate with foreign languages, through Haskell foreign function interface (FFI), it is possible to set up co-simulation. The Verilog Procedural Interface (VPI), as defined in the IEEE 1364 standard, is used to set-up the communication and to control a Verilog simulator. -
An Open-Source Python-Based Hardware Generation, Simulation
An Open-Source Python-Based Hardware Generation, Simulation, and Verification Framework Shunning Jiang Christopher Torng Christopher Batten School of Electrical and Computer Engineering, Cornell University, Ithaca, NY { sj634, clt67, cbatten }@cornell.edu pytest coverage.py hypothesis ABSTRACT Host Language HDL We present an overview of previously published features and work (Python) (Verilog) in progress for PyMTL, an open-source Python-based hardware generation, simulation, and verification framework that brings com- FL DUT pelling productivity benefits to hardware design and verification. CL DUT generate Verilog synth RTL DUT PyMTL provides a natural environment for multi-level modeling DUT' using method-based interfaces, features highly parametrized static Sim FPGA/ elaboration and analysis/transform passes, supports fast simulation cosim ASIC and property-based random testing in pure Python environment, Test Bench Sim and includes seamless SystemVerilog integration. Figure 1: PyMTL’s workflow – The designer iteratively refines the hardware within the host Python language, with the help from 1 INTRODUCTION pytest, coverage.py, and hypothesis. The same test bench is later There have been multiple generations of open-source hardware reused for co-simulating the generated Verilog. FL = functional generation frameworks that attempt to mitigate the increasing level; CL = cycle level; RTL = register-transfer level; DUT = design hardware design and verification complexity. These frameworks under test; DUT’ = generated DUT; Sim = simulation. use a high-level general-purpose programming language to ex- press a hardware-oriented declarative or procedural description level (RTL), along with verification and evaluation using Python- and explicitly generate a low-level HDL implementation. Our pre- based simulation and the same TB. -
Technical Competencies and Professional Skills
TECHNICAL COMPETENCIES AND PROFESSIONAL SKILLS Applied Mathematics Technical Skills: data visualization and analysis, SQL, finance and accounting Programming Languages: R, MATLAB, C++, Java, Python Markup Languages: LaTeX, HTML, CSS Software: Microsoft Office (Excel, Office, Word), XCode, Visual Studio Note: Skills, software, and languages are dependent on elective taken, computer selection, and class year. Applied Sciences Instrumentation: UV/Vis spectroscopy, NMR spectroscopy, IR spectroscopy, GC-MS, LC-MS, thermocycler, nucleic acid sequencer, microplate reader, cryocooler Lab Techniques: Gel electrophoresis and SDS-PAGE, Western blotting, primer design and Polymerase Chain Reaction (PCR), QPCR, sterile lab technique, cell culture, nucleic acid isolation and purification, protein isolation and purification (chromatography, centrifugation, dialysis), enzyme thermodynamics and kinetics, transfection and transformation, chemical synthesis and purification (distillation, extraction, chromatography, rotary evaporator, crystallization), inert atmosphere and Schlenk line techniques, titration, dissection of preserved specimens, four-probe electrical measurement, Bragg diffraction Competencies: Application of the scientific method, Scientific writing and oral communication Software and computational skills: Microsoft Office (Word, Excel, Powerpoint), ChemDraw, PyMol, TopSpin, Java, Protein DataBank (PDB), NCBI suite (including BLAST, GenBank), Orca Quantum Chemistry software, LoggerPro, LabView Architecture Design Skills: Multi-scale civic -
Intro to Programmable Logic and Fpgas
CS 296-33: Intro to Programmable Logic and FPGAs ADEL EJJEH UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN © Adel Ejjeh, UIUC, 2015 2 Digital Logic • In CS 233: • Logic Gates • Build Logic Circuits • Sum of Products ?? F = (A’.B)+(B.C)+(A.C’) A B Black F Box C © Adel Ejjeh, UIUC, 2015 3 Programmable Logic Devices (PLDs) PLD PLA PAL CPLD FPGA (Programmable (Programmable (Complex PLD) (Field Prog. Logic Array) Array Logic) Gate Array) •2-level structure of •Enhanced PLAs •For large designs •Has a much larger # of AND-OR gates with reduced costs •Collection of logic blocks with programmable multiple PLDs with •Larger interconnection connections an interconnection networK structure •Largest manufacturers: Xilinx - Altera Slide taken from Prof. Chehab, American University of Beirut © Adel Ejjeh, UIUC, 2015 4 Combinational Programmable Logic Devices PLAs, CPLDs © Adel Ejjeh, UIUC, 2015 5 Programmable Logic Arrays (PLAs) • 2-level AND-OR device • Programmable connections • Used to generate SOP • Ex: 4x3 PLA Slide adapted from Prof. Chehab, American University of Beirut © Adel Ejjeh, UIUC, 2015 6 PLAs contd • O1 = I1.I2’ + I4.I3’ • O2 = I2.I3.I4’ + I4.I3’ • O3 = I1.I2’ + I2.I1’ Slide adapted from Prof. Chehab, American University of Beirut © Adel Ejjeh, UIUC, 2015 7 Programmable Array Logic (PALs) • More Versatile than PLAs • User Programmable AND array followed by fixed OR gates • Flip-flops/Buffers with feedback transforming output ports into I/O ports © Adel Ejjeh, UIUC, 2015 8 Complex PLDs (CPLD) • Programmable PLD blocks (PALs) I/O Block I/O I/O -
A Pythonic Approach for Rapid Hardware Prototyping and Instrumentation
A Pythonic Approach for Rapid Hardware Prototyping and Instrumentation John Clow, Georgios Tzimpragos, Deeksha Dangwal, Sammy Guo, Joseph McMahan and Timothy Sherwood University of California, Santa Barbara, CA, 93106 USA Email: fjclow, gtzimpragos, deeksha, sguo, jmcmahan, [email protected] Abstract—We introduce PyRTL, a Python embedded hardware To achieve these goals, PyRTL intentionally restricts users design language that helps concisely and precisely describe to a set of reasonable digital design practices. PyRTL’s small digital hardware structures. Rather than attempt to infer a and well-defined internal core structure makes it easy to add good design via HLS, PyRTL provides a wrapper over a well- defined “core” set of primitives in a way that empowers digital new functionality that works across every design, including hardware design teaching and research. The proposed system logic transforms, static analysis, and optimizations. Features takes advantage of the programming language features of Python such as elaboration-through-execution (e.g. introspection), de- to allow interesting design patterns to be expressed succinctly, and sign and simulation without leaving Python, and the option encourage the rapid generation of tooling and transforms over to export to, or import from, common HDLs (Verilog-in via a custom intermediate representation. We describe PyRTL as a language, its core semantics, the transform generation interface, Yosys [1] and BLIF-in, Verilog-out) are also supported. More and explore its application to several different design patterns and information about PyRTL’s high level flow can be found in analysis tools. Also, we demonstrate the integration of PyRTL- Figure 1. generated hardware overlays into Xilinx PYNQ platform. -
NESS Esk a 2005.0034090 a 22005 Sato Et
US007 185309B1 (12) United States Patent (10) Patent No.: US 7,185,309 B1 Kulkarni et al. (45) Date of Patent: Feb. 27, 2007 (54) METHOD AND APPARATUS FOR 2004/0006584 A1 1/2004 Vandeweerd APPLICATION-SPECIFIC PROGRAMMABLE 2004/O128120 A1 7/2004 Coburn et al. NESS Esk A 2005.00340902005/0114593 A1A 220055/2005 SatoCassell et al.et al. (75) Inventors: Chidamber R. Kulkarni, San Jose, CA 2005/0172085 A1 8/2005 Klingman (US); Gordon J. Brebner, Monte 2005/0172087 A1 8/2005 Klingman Sereno, CA (US); Eric R. Keller, 2005/0172088 A1 8/2005 Klingman Boulder, CO (US); Philip B. 2005/0172089 A1 8/2005 Klingman James-Roxby, Longmont, CO (US) 2005/0172090 A1 8/2005 Klingman O O 2005/0172289 A1 8/2005 Klingman (73) Assignee: Xilinx, Inc., San Jose, CA (US) 2005/0172290 A1 8/2005 Klingman (*) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 (21) Appl. No.: 10/769,591 OTHER PUBLICATIONS (22) Filed: Jan. 30, 2004 U.S. Appl. No. 10/769,330, filed Jan. 30, 2004, James-Roxby et al. (51) Int. Cl. (Continued) G06F 7/50 (2006.01) Primary Examiner Thuan Do (52) U.S. Cl. ............................................. 716/18: 718/2 Assistant Examiner Binh Tat (58) Field of Classification Search .................. 716/18, (74) Attorney, Agent, or Firm—Robert Brush 716/2, 3: 709/217: 71.9/313 See application file for complete search history. (57) ABSTRACT (56) References Cited U.S. PATENT DOCUMENTS Programmable architecture for implementing a message 5,867,180 A * 2/1999 Katayama et al. -
Standby Power Management Architecture for Deep- Submicron Systems
Standby Power Management Architecture for Deep- Submicron Systems Michael Alan Sheets Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2006-70 http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-70.html May 19, 2006 Copyright © 2006, 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. Standby Power Management Architecture for Deep-Submicron Systems by Michael Alan Sheets B.S.C.E. (Georgia Institute of Technology) 1999 M.S. (University of California, Berkeley) 2003 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Engineering-Electrical Engineering and Computer Sciences in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor Jan Rabaey, Chair Professor Robert Brodersen Professor Paul Wright Spring 2006 The dissertation of Michael Alan Sheets is approved: Chair Date Date Date University of California, Berkeley Spring 2006 Standby Power Management Architecture for Deep-Submicron Systems Copyright 2006 by Michael Alan Sheets 1 Abstract Standby Power Management Architecture for Deep-Submicron Systems by Michael Alan Sheets Doctor of Philosophy in Engineering-Electrical Engineering and Computer Sciences University of California, Berkeley Professor Jan Rabaey, Chair In deep-submicron processes a signi¯cant portion of the power budget is lost in standby power due to increasing leakage e®ects. -
DS5000FP Soft Microprocessor Chip
DS5000FP Soft Microprocessor Chip www.maxim-ic.com FEATURES PIN CONFIGURATION 8051-Compatible Microprocessor Adapts to Its Task TOP VIEW − Accesses between 8kB and 64kB of nonvolatile SRAM LE BD6 PSEN BD5 P2.7/A15 BD4 − In-system programming via on-chip serial BA11 P0.5/AD5 CE2 P0.6/AD6 BA10 P0.7/AD7 CE1 EA N.C. BD7 A port − Can modify its own program or data 80 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 P0.4/AD4 1 64 P2.6/A14 2 N.C. 63 N.C. memory 3 62 N.C. N.C. BA9 4 61 BD3 − Accesses memory on a separate byte-wide P0.3/AD3 5 60 P2.5/A13 bus BA8 6 59 BD2 P0.2/AD2 7 58 P2.4/A12 Crash-Proof Operation BA13 8 57 BD1 P0.1/AD1 9 56 P2.3/A11 R/W 10 55 BD0 − Maintains all nonvolatile resources for 11 54 P0.0/AD0 VLI VCC0 12 53 GND over 10 years VCC 13 DS5000FP 52 GND 14 51 − Power-fail Reset VCC P2.2/A10 P1.0 15 50 P2.1/A9 BA14 16 49 P2.0/A8 − Early Warning Power-fail Interrupt P1.1 17 48 XTAL1 BA12 18 47 XTAL2 19 − Watchdog Timer P1.2 46 P3.7/RD 20 45 BA7 P3.6/WR − User-supplied lithium battery backs user P1.3 21 44 P3.5/T1 N.C. 22 43 N.C. SRAM for program/data storage N.C. 23 42 N.C. -
Nanoelectronic Mixed-Signal System Design
Nanoelectronic Mixed-Signal System Design Saraju P. Mohanty Saraju P. Mohanty University of North Texas, Denton. e-mail: [email protected] 1 Contents Nanoelectronic Mixed-Signal System Design ............................................... 1 Saraju P. Mohanty 1 Opportunities and Challenges of Nanoscale Technology and Systems ........................ 1 1 Introduction ..................................................................... 1 2 Mixed-Signal Circuits and Systems . .............................................. 3 2.1 Different Processors: Electrical to Mechanical ................................ 3 2.2 Analog Versus Digital Processors . .......................................... 4 2.3 Analog, Digital, Mixed-Signal Circuits and Systems . ........................ 4 2.4 Two Types of Mixed-Signal Systems . ..................................... 4 3 Nanoscale CMOS Circuit Technology . .............................................. 6 3.1 Developmental Trend . ................................................... 6 3.2 Nanoscale CMOS Alternative Device Options ................................ 6 3.3 Advantage and Disadvantages of Technology Scaling . ........................ 9 3.4 Challenges in Nanoscale Design . .......................................... 9 4 Power Consumption and Leakage Dissipation Issues in AMS-SoCs . ................... 10 4.1 Power Consumption in Various Components in AMS-SoCs . ................... 10 4.2 Power and Leakage Trend in Nanoscale Technology . ........................ 10 4.3 The Impact of Power Consumption -
Review of FPD's Languages, Compilers, Interpreters and Tools
ISSN 2394-7314 International Journal of Novel Research in Computer Science and Software Engineering Vol. 3, Issue 1, pp: (140-158), Month: January-April 2016, Available at: www.noveltyjournals.com Review of FPD'S Languages, Compilers, Interpreters and Tools 1Amr Rashed, 2Bedir Yousif, 3Ahmed Shaban Samra 1Higher studies Deanship, Taif university, Taif, Saudi Arabia 2Communication and Electronics Department, Faculty of engineering, Kafrelsheikh University, Egypt 3Communication and Electronics Department, Faculty of engineering, Mansoura University, Egypt Abstract: FPGAs have achieved quick acceptance, spread and growth over the past years because they can be applied to a variety of applications. Some of these applications includes: random logic, bioinformatics, video and image processing, device controllers, communication encoding, modulation, and filtering, limited size systems with RAM blocks, and many more. For example, for video and image processing application it is very difficult and time consuming to use traditional HDL languages, so it’s obligatory to search for other efficient, synthesis tools to implement your design. The question is what is the best comparable language or tool to implement desired application. Also this research is very helpful for language developers to know strength points, weakness points, ease of use and efficiency of each tool or language. This research faced many challenges one of them is that there is no complete reference of all FPGA languages and tools, also available references and guides are few and almost not good. Searching for a simple example to learn some of these tools or languages would be a time consuming. This paper represents a review study or guide of almost all PLD's languages, interpreters and tools that can be used for programming, simulating and synthesizing PLD's for analog, digital & mixed signals and systems supported with simple examples. -
Microprocessor Design
Microprocessor Design en.wikibooks.org March 15, 2015 On the 28th of April 2012 the contents of the English as well as German Wikibooks and Wikipedia projects were licensed under Creative Commons Attribution-ShareAlike 3.0 Unported license. A URI to this license is given in the list of figures on page 211. If this document is a derived work from the contents of one of these projects and the content was still licensed by the project under this license at the time of derivation this document has to be licensed under the same, a similar or a compatible license, as stated in section 4b of the license. The list of contributors is included in chapter Contributors on page 209. The licenses GPL, LGPL and GFDL are included in chapter Licenses on page 217, since this book and/or parts of it may or may not be licensed under one or more of these licenses, and thus require inclusion of these licenses. The licenses of the figures are given in the list of figures on page 211. This PDF was generated by the LATEX typesetting software. The LATEX source code is included as an attachment (source.7z.txt) in this PDF file. To extract the source from the PDF file, you can use the pdfdetach tool including in the poppler suite, or the http://www. pdflabs.com/tools/pdftk-the-pdf-toolkit/ utility. Some PDF viewers may also let you save the attachment to a file. After extracting it from the PDF file you have to rename it to source.7z. -
Myhdl Manual Release 0.11
MyHDL manual Release 0.11 Jan Decaluwe April 10, 2020 Contents 1 Overview 1 2 Background information3 2.1 Prerequisites.......................................3 2.2 A small tutorial on generators.............................3 2.3 About decorators.....................................4 3 Introduction to MyHDL7 3.1 A basic MyHDL simulation...............................7 3.2 Signals and concurrency.................................8 3.3 Parameters, ports and hierarchy............................9 3.4 Terminology review................................... 11 3.5 Some remarks on MyHDL and Python........................ 12 3.6 Summary and perspective................................ 12 4 Hardware-oriented types 13 4.1 The intbv class..................................... 13 4.2 Bit indexing........................................ 14 4.3 Bit slicing......................................... 15 4.4 The modbv class..................................... 17 4.5 Unsigned and signed representation.......................... 18 5 Structural modeling 19 5.1 Introduction........................................ 19 5.2 Conditional instantiation................................ 19 5.3 Converting between lists of signals and bit vectors................. 21 5.4 Inferring the list of instances.............................. 22 6 RTL modeling 23 6.1 Introduction........................................ 23 6.2 Combinatorial logic................................... 23 6.3 Sequential logic...................................... 25 6.4 Finite State Machine modeling............................