• DocumentCode
    2807356
  • Title

    Automatic Generation of High Performance Embedded Memory Models for PowerPC Microprocessors

  • Author

    Bhadra, Jayanta ; Abadir, Magdy S. ; Burgess, David ; Trofimova, Ekaterina

  • fYear
    2005
  • fDate
    3-5 Nov. 2005
  • Firstpage
    111
  • Lastpage
    118
  • Abstract
    Embedded memories form a crucial part in the design of modern high performance microprocessors. The number of transistors in memories forms a majority of the transistors in a typical high performance microprocessor. Therefore, modeling embedded memories is an important challenge in high performance microprocessor design. A typical design process involves a multiplicity of interacting methodologies - simulation, formal verification, design for test, emulation etc. Memory models are needed for each of these methodologies. This complicates the process of modeling memories. The authors present a tool called MemGen that automates memory model generation for all methodologies. It has been used in-house in Motorola Inc. and then later in Freescale Semiconductor Inc. in all high performance design projects. The authors present result obtained by using MemGen-generated embedded memories in real life design projects of PowerPCreg G2 and G4 microprocessors
  • Keywords
    automatic test pattern generation; embedded systems; integrated memory circuits; microprocessor chips; Freescale Semiconductor Inc.; MemGen; Motorola Inc.; PowerPC G2 microprocessors; PowerPC G4 microprocessors; PowerPC microprocessors; automatic generation; formal verification; high performance embedded memory models; memory model generation; microprocessor design; real life design projects; Automatic test pattern generation; Circuit testing; Computer bugs; Distributed power generation; Emulation; Formal verification; Logic testing; Microprocessors; Power generation; Read-write memory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Microprocessor Test and Verification, 2005. MTV '05. Sixth International Workshop on
  • Conference_Location
    Austin, TX
  • ISSN
    1550-4093
  • Print_ISBN
    0-7695-2627-6
  • Type

    conf

  • DOI
    10.1109/MTV.2005.9
  • Filename
    4022237