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EE 587 SoC Design & Test Partha Pande School of EECS Washington State University

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Presentation on theme: "EE 587 SoC Design & Test Partha Pande School of EECS Washington State University"— Presentation transcript:

1 EE 587 SoC Design & Test Partha Pande School of EECS Washington State University pande@eecs.wsu.edu

2 Test Methodologies, and Yield Reference: “Essentials of Electronic Testing” by Bushnell and Agrawal

3 Introduction n VLSI realization process n Verification and test n Ideal and real tests n Costs of testing

4 VLSI Realization Process Determine requirements Write specifications Design synthesis and Verification Fabrication Manufacturing test Chips to customer Customer’s need Test development

5 Definitions n Design synthesis: Given an I/O function, develop a procedure to manufacture a device using known materials and processes. n Verification: Predictive analysis to ensure that the synthesized design, when manufactured, will perform the given I/O function. n Test: A manufacturing step that ensures that the physical device, manufactured from the synthesized design, has no manufacturing defect.

6 Verification vs. Test n Verifies correctness of design. n Performed by simulation, hardware emulation, or formal methods. n Performed once prior to manufacturing. n Responsible for quality of design. n Verifies correctness of manufactured hardware. n Two-part process: 1. Test generation: software process executed once during design 2. Test application: electrical tests applied to hardware n Test application performed on every manufactured device. n Responsible for quality of devices.

7 Problems of Ideal Tests n Ideal tests detect all defects produced in the manufacturing process. n Ideal tests pass all functionally good devices. n Very large numbers and varieties of possible defects need to be tested. n Difficult to generate tests for some real defects. Defect-oriented testing is an open problem.

8 Defect vs. Fault  To become a fault, the defect needs to connect two disjoint conductors or disconnect a continuous pattern

9 Wafer Defect Map  Faults are a percentage of defects  Same distribution with fewer points

10 Real Tests n Based on analyzable fault models, which may not map on real defects. n Incomplete coverage of modeled faults due to high complexity. n Some good chips are rejected. The fraction (or percentage) of such chips is called the yield loss. n Some bad chips pass tests. The fraction (or percentage) of bad chips among all passing chips is called the defect level.

11 Testing as Filter Process Fabricated chips Good chips Defective chips Prob (good) = y Prob(bad) = 1- y Prob(pass test) = high Prob(fail test) = high Prob(fail test) = low Prob(pass test) = low Mostly good chips Mostly bad chips

12 Costs of Testing n Design for testability (DFT) Chip area overhead and yield reduction Performance overhead n Software processes of test Test generation and fault simulation Test programming and debugging n Manufacturing test Automatic test equipment (ATE) capital cost Test center operational cost

13 Design for Testability (DFT) DFT refers to hardware design styles or added hardware that reduces test generation complexity. Motivation: Test generation complexity increases exponentially with the size of the circuit. Logic block A Logic block B PI PO Test input Test output Int. bus Example: Test hardware applies tests to blocks A and B and to internal bus; avoids test generation for combined A and B blocks.

14 Present and Future* Transistors/sq. cm 4 - 10M 18 - 39M Pin count 100 - 900 160 - 1475 Clock rate (MHz) 200 - 730 530 - 1100 Power (Watts) 1.2 - 61 2 - 96 Feature size (micron) 0.25 - 0.15 0.13 - 0.10 1997 -20012003 - 2006 * SIA Roadmap, IEEE Spectrum, July 1999

15 Cost of Manufacturing Testing in 2000AD n 0.5-1.0GHz, analog instruments,1,024 digital pins: ATE purchase price = $1.2M + 1,024 x $3,000 = $4.272M n Running cost (five-year linear depreciation) = Depreciation + Maintenance + Operation = $0.854M + $0.085M + $0.5M = $1.439M/year n Test cost (24 hour ATE operation) = $1.439M/(365 x 24 x 3,600) = 4.5 cents/second

16 Roles of Testing n Detection: Determination whether or not the device under test (DUT) has some fault. n Diagnosis: Identification of a specific fault that is present on DUT. n Device characterization: Determination and correction of errors in design and/or test procedure. n Failure mode analysis (FMA): Determination of manufacturing process errors that may have caused defects on the DUT.

17 Yield Analysis & Product Quality n Yield and manufacturing cost n Clustered defect yield formula n Yield improvement n Defect level n Test data analysis n Example: SEMATECH chip n Summary

18 VLSI Chip Yield n A manufacturing defect is a finite chip area with electrically malfunctioning circuitry caused by errors in the fabrication process. n A chip with no manufacturing defect is called a good chip. n Fraction (or percentage) of good chips produced in a manufacturing process is called the yield. Yield is denoted by symbol Y. n Cost of a chip: Cost of fabricating and testing a wafer -------------------------------------------------------------------- Yield x Number of chip sites on the wafer

19 Clustered VLSI Defects Wafer Defects Faulty chips Good chips Unclustered defects Wafer yield = 12/22 = 0.55 Clustered defects (VLSI) Wafer yield = 17/22 = 0.77

20 Yield Parameters n Defect density (d ) = Average number of defects per unit of chip area n Chip area (A) Clustering parameter (  ) n Negative binomial distribution of defects, p (x ) = Prob (number of defects on a chip = x )  (  +x ) (Ad /  ) x = -------------. ---------------------- x !  (  ) (1+Ad /  )  +x where  is the gamma function  =0, p (x ) is a delta function (max. clustering)  =, p (x ) is Poisson distr. (no clustering) 

21 Yield Equation Y = Prob ( zero defect on a chip ) = p (0) Y = ( 1 + Ad /  )  Example: Ad = 1.0,  = 0.5, Y = 0.58 Unclustered defects:  =, Y = e - Ad Example: Ad = 1.0,  =, Y = 0.37 too pessimistic !  

22 Defect Level or Reject Ratio n Defect level (DL) is the ratio of faulty chips among the chips that pass tests. n DL is measured as parts per million (ppm). n DL is a measure of the effectiveness of tests. n DL is a quantitative measure of the manufactured product quality. For commercial VLSI chips a DL greater than 500 ppm is considered unacceptable.

23 Determination of DL n From field return data: Chips failing in the field are returned to the manufacturer. The number of returned chips normalized to one million chips shipped is the DL. n From test data: Fault coverage of tests and chip fallout rate are analyzed. A modified yield model is fitted to the fallout data to estimate the DL.

24 Modified Yield Equation n Three parameters: n Fault density, f = average number of stuck-at faults per unit chip area Fault clustering parameter,  n Stuck-at fault coverage, T n The modified yield equation: Y (T ) = (1 + TAf /  ) -  Assuming that tests with 100% fault coverage (T =1.0) remove all faulty chips, Y = Y (1) = (1 + Af /  ) - 

25 Defect Level Y (T ) - Y (1) DL (T ) = -------------------- Y (T ) (  + TAf )  = 1 - -------------------- (  + Af )  Where T is the fault coverage of tests, Af is the average number of faults on the chip of area A,  is the fault clustering parameter. Af and  are determined by test data analysis.

26 Test Coverage from Fault Simulator Stuck-at fault coverage Vector number

27 Measured Chip Fallout Vector number Measured chip fallout

28 Model Fitting Y (T ) for Af = 2.1 and  = 0.083 Measured chip fallout Y (1) = 0.7623 Chip fallout and computed 1-Y (T ) Stuck-at fault coverage, T Chip fallout vs. fault coverage

29 Computed DL Stuck-at fault coverage (%) Defect level in ppm 237,700 ppm (Y = 76.23%)

30 Summary VLSI yield depends on two process parameters, defect density (d ) and clustering parameter (  ) n Yield drops as chip area increases; low yield means high cost n Fault coverage measures the test quality n Defect level (DL) or reject ratio is a measure of chip quality n DL can be determined by an analysis of test data n For high quality: DL < 500 ppm, fault coverage ~ 99%


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