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LARGE ARRAY COMPILER FOR AUTOMATIC SRAM GENERATION AND MODELING

Giuseppe Ferotti

LARGE ARRAY COMPILER FOR AUTOMATIC SRAM GENERATION AND MODELING.

Rel. Danilo Demarchi, Timothy Constandinou. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2021

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Abstract:

ICs designers frequently employ memory compilers to produce the memory with desired dimensions and configurations rapidly. Memory design methodology in the academic environment is often insufficient: most process design kits (PDKs) does not include a memory compiler. Besides, the customization of memory and cell dimensions and specific peripherals is constrained by these industrial options, and the internal function/layout is commonly inaccessible. Since many different size arrays can be produced (mainly constrained by system data storage need, area, power, and performance), it is practically impossible to have a perfectly tailored bit-cell for the specific system requirements with modern compilers. This project aims to overcome this problem by designing a simple, modular and flexible SRAM memory compiler that uses a 6T-SRAM cell in 180nm TSMC technology with customizable transistor widths: in this way, the system designer can select the desired transistor sizes in the cell, optimized for the system requirements and size of the array. This bottom-up approach permits to fulfil designer's specific needs without renouncing flexibility, transparency and integration with IC design existing tools. To simulate an array properly, the essential column peripheral circuits (precharge circuit, sense amplifier and write driver) are analyzed and designed. Since Cadence Virtuoso suite is one of the primary tool used in the industry, SKILL scripting language is used to develop the compiler software. The software performs cell and peripherals schematic creation, cell layout DRC, LVS and parasitic extraction. A complete write/read SPICE simulation of a test-bench with the desired array and peripheral circuits is then performed using an OCEAN script, and the results are stored. The user can also decide to use or not the extracted cell-view to speed up simulation time.

Relatori: Danilo Demarchi, Timothy Constandinou
Anno accademico: 2020/21
Tipo di pubblicazione: Elettronica
Numero di pagine: 88
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-29 - INGEGNERIA ELETTRONICA
Ente in cotutela: Imperial College London (REGNO UNITO)
Aziende collaboratrici: Imperial College London
URI: http://webthesis.biblio.polito.it/id/eprint/17815
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