USING JMP TO OPTIMIZE PERFORMANCESENSITIVE SEMICONDUCTOR PRODUCTS SCOTT

USING JMP TO OPTIMIZE PERFORMANCE-SENSITIVE SEMICONDUCTOR PRODUCTS SCOTT RUBEL TODD JACOBS JIM NELSON EXTERNAL USE DISCOVERY SUMMIT 2016

Overview Modern chip designs have multiple IP components with different process, voltage, temperature sensitivities • Optimizing mix to different customer requirements (bins) across process window has huge gross margin impact • Monte Carlo simulation optimal for simulating speed-power distribution and bin mix under different conditions • − Large number of statistical parameters (40 – 60 typically, plus covariance matrix) and bin limits (~20 -100) − Consistent − JMP • 1 extraction, documentation critical to manage these scripting provides statistical tools + journaling = unique capability Fast execution (1 -5 minutes) and consistent documentation allow comparison of multiple business cases EXTERNAL USE

Simulation Flow Vary scaling or limits to explore different process scenarios, evaluate profitability • Software can simulate multiple limit scenarios in one run • 2 EXTERNAL USE Simulated Cloud Distributions Process Window Optimal Spec, Process Limits Alternate scenarios Descriptive Statistics Alternate scenarios Product Data or Design Inputs

Speed-Power Distributions • Frequency is (nearly always) a linear function of log(static current), plus noise − 3 EXTERNAL USE 3 parameters for power, plus 3 per frequency

Speed-Power Distributions • 4 EXTERNAL USE “Distribution” is fraction of die meeting minimum speed, maximum power specs for a given spec, voltage

Speed-Power Distributions • Testing spec at multiple voltages improves distribution − 5 EXTERNAL USE Lighter (darker) regions show additional die that will pass when tested to higher (lower) voltage

Speed-Power Distributions • 6 EXTERNAL USE Die that fail one spec can still pass another − Red region: high-speed, high-power spec − Blue region: low-speed, low-power spec

Speed-Power Distributions • • 7 EXTERNAL USE Some die can pass multiple specs − Shaded areas show die which can pass combinations of green, red, and blue specs − Known as “combination (combo)” bins − Can be used to flex supply from one bin to another Complex boundaries require custom logic to handle correctly − Logical OR across voltages − Logical AND across patterns and temperatures

Pass/Fail, Binning Calculations Overall rate can consider either all possible die which pass bin, or assign die to first bin passed • Logic is straightforward, but tricky. Scripting ensures it is done right every time. • Pass/Fail results for multiple bins, multiple die 8 EXTERNAL USE

Sample Input Configuration File Statistical parameters saved to configuration file after initial run Configuration parameters for simulation runs Limits for each pattern, temperature, voltage combination 9 EXTERNAL USE

Data validity checks • JMP scripting ensures common analysis errors are avoided: − Perfectly correlated parameters − Nonphysical correlations − Bin/pattern/grouping − Missing limits − Missing source data − Missing/invalid − Missing parameters grouping parameters (voltage, temperature, pattern) − Missing/duplicate − Missing • 10 combinations that guarantee zero distribution always Fmax pattern names test sort order Red items are particularly easy to miss: simulation may run but produce deceptive results EXTERNAL USE

Journal Output X-Y plot shows simulation for target process condition Input Table: /C: /Documents/data extracts/Feb 2015/Test. jmp Each point represents bin distribution for a particular process condition Power limit voltage sensitivities documented • Journal file contains full configuration table, linear Fmax fit equations, and covariance tables • X-Y plots can show any two input parameters desired, with appropriate limits • Data tables for target process simulation and distributions automatically saved to specified location 11 EXTERNAL USE

Scenario Modeling: Variance Scaling Factory process improvements affect bin distribution through tighter variance • Tool has Variance Scaling parameter to model this; included in standard documentation • Generating plots requires separate runs • 12 EXTERNAL USE

Scenario Modeling: Test Program Changes 2 1 3 4 5 Original sort order: orange, red, light green, dark green, blue • Curves at right show yield to each bin given this order • − Sum 13 is 100% (die not double-counted) EXTERNAL USE

Scenario Modeling: Test Program Changes 1 2 4 3 5 Consider swapping red and dark green bins in sort order • New sort order: orange, dark green, light green, red, blue • Bin distributions change to new plot • Note that light green distribution drops to zero while dark green increases dramatically − Red bin distribution also reduced − 14 EXTERNAL USE

Scenario Modeling: Pre-Assembly Speed Sorting • Based on wafer speed testing these units are built in a different package 15 EXTERNAL USE Distributions for single package look very different than overall mix Script codes simulated die based on bin assignment, allowing visual assessment of how parameters align with binning

Scenario Modeling: Variable power limits B 1 limits can be varied in single iterate run • Here 11 different values of power limit used • Distribution table can be used to create other graphs as desired • − Example 16 shows impact of power limit on supply to Bin 1 EXTERNAL USE

Scenario Modeling: Frequency Loss Tool evaluates different aspects of distribution as frequency is impacted: process target must be increased, process window shrinks, and maximum distribution drops • Simulation shows up to ~40 MHz of speed loss tolerable. Key input for Design, Marketing teams • 17 EXTERNAL USE

Summary Built-in validation manages complex inputs • Math is taken care of for users, allowing focus on results • Standard output ensures consistent, thorough documentation • Can be seeded with data prior to tapeout to ensure successful product launch • − Significant cost savings, revenue improvement − Concrete feedback to Marketing and Design teams enhances customer engagement • Tool allows rapid evaluation of different production scenarios − Easy 18 to perform sensitivity analyses EXTERNAL USE