Benchmarking Microelectronics Innovation: Understanding Moore’s Law and Semiconductor Price Trends

Kenneth Flamm

Technology and Public Policy Program

Lyndon B. Johnson School of Public Affairs

University of Texas at Austin

kflamm@mail.utexas.edu

Outline

Why Do We Care? Moore’s Law The Economics of Moore’s Law The Economic Impact of Moore’s Law Benchmarking Moore’s Law Tinkering with Moore’s Law Point of Inflection? Official Data on Semiconductor Prices Better Benchmarking

Key Economic Features of the Semiconductor Industry Extremely rapid technical progress Large R&D Investments Learning Economies Capital Intensity Capacity Constraints, Long

Gestation Lags One Complicated Industry

Why Do We Care?

Now largest U.S. manufacturing industry Measured by value added

One 4-digit manufacturing industry now almost 1% U.S. GDP

Most important input to other industries we care a lot about Computers, communications Big impact on GDP, productivity growth See Jorgenson AEA 2001 Presidential

Address.

Changing Size: U.S. semiconductor mfg val added vs. GDP 1958 1965 1975 1985 1995 1997

.04% .09% .13% .26% .70% .77%

Moore’s Law

In the beginning: the original law 2x devices/chip every 12 months ca. 1965

Moore rev.2 2x devices/chip every 18 months ca. 1975

Self-fulfilling prophecy? “it happened because everyone believed

it was going to happen” The receding brick wall

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Figure 1The Original "Moore's Law" Plot

From Electronics April 1965Lo

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Economics of Translating Moore into $ and ¢

$/device =

$ processing cost area silicon

Area/chip_____________________ Devices/chip

New “technology node” every 3 years

Lithography advance means .5X area perchip feature

Moore’s law 4x devices/chip every 3 years

Would predict Area/chip 2X every 3 years

$ processing cost/wafer area roughly constant

CADR = -21%

An Economist’s Default Corollary to Moore’s Law:Moore’s Law + constant wafer processing cost + new technology node every 3 years=-21 % CADR

The Ingenuity (DRAM) Corollary: Instead of doubling chip size, use ingenuity to

increase it only Z (Z < 2) times real recent example (DRAMs), Z=1.37 3-D device structures

Implications of ingenuity for DRAMs recently, CADR = -30% for DRAMs, in 70s and 80s, wafer processing

cost also fell, CADR more like -37% Japan/VLSI project, competition impact?

Another example is ASICs, more rapid leading edge technology adoption transitory impact on CADR

Benchmarking Moore’s law: Differences in Semiconductor Price Movements Are HUGE

Source: Aizcorbe, Flamm, and Khurshid (2001).

Implications for Input Prices in Different User Industries Also Great

Source: Aizcorbe, Flamm, and Khurshid (2001).

Accounting for the economic impact of Moore’s Law

The standard model Estimated cost decline Estimated price elasticity Calculations of benefits

The Standard Model: Consumer’s Surplus

Figure 5Social Benefit From a Decline in Semiconductor Price

Dollars

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The Numbers: 

Summary of Consumer Welfare Calculations

 

Benefit in 1995 of 

Billion $ 

Percent ofGDP

Percent of 1995 GDP Growth

 

1 year’s price decline 20 years’ price declines 30 years’ price declines 

1.8  378 1503

0.16  5.2  21

8  260 1039

Magnitudes

1 year’s tech improvement yields .16% GDP …forever

20 years’ tech improvement would cost you about 5 percent of GDP if rolled back

If you’re feeling really brave, roll the clock back 30 years and you shave off up to 20 percent of GDP!

More Comparisons

Other well-studied cases-- the railroads in the 19th century

The old guys vs. the new guys: a historical parable

Tinkering with Moore’s Law: The Technological Acceleration (Sematech Roadmap) Corollary Suppose new technology node every 2

years instead of 3 Industry coordinated push through

Sematech in late 1990s Competitive pressures also pushed

New default (2X chip size) CADR = -29%

New DRAM (1.37X chip size) CADR = -41%

Constant chip size (1X chip size) CADR = -50%

         

 

Decline Rates in Price-Performance

  Percent/Year

Microprocessors, 1975-85 -37.5Hedonic Index 1985-94 -26.7

DRAM Memory, 1975-85 -40.4Fisher Matched Model 1985-94 -19.9 DRAMs, Fisher Matched Model, Quarterly Data

91:2-95:4 -11.995:4-98:4 -64.0

Intel Microprocessors, Fisher Matched Model, Quarterly Data

93:1-95:4 -47.095:4-99:4 -61.6

Decline Rates in Price-Performance

  Percent/Year

Microprocessors, 1975-85 -37.5Hedonic Index 1985-94 -26.7

DRAM Memory, 1975-85 -40.4Fisher Matched Model 1985-94 -19.9 DRAMs, Fisher Matched Model, Quarterly Data

91:2-95:4 -11.995:4-98:4 -64.0

Intel Microprocessors, Fisher Matched Model, Quarterly Data

93:1-95:4 -47.095:4-99:4 -61.6Sources: Flamm (1997); Aizcorbe, Corrado, and Doms (2000)

Point of Inflection?

Change of Pace?

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Implications of This Interpretation of Moore’s Law Ultra-high rate of innovation in late 1990’s

temporary Transitory factors increased innovation

above long-term sustainable rates Shortened product lives Intensified competition More rapid adoption of leading edge

processes in other products Future CADR will look more like –40%

than –60%+ Economic impacts may decline to lower

but more sustainable rates

Benchmarking Moore’s Law in the U.S.: Official Statistics on Chip Prices BEA got ball rolling, taken over by others BLS-- Much improved for DRAMs and

Microprocessors, not so hot for other products Data sources a concern Documentation a concern

Fed Reserve has stealth program, currently best numbers in town Data sources a concern Weights a concern Possible application in estimating capacity a

big concern Access/availability outside Fed a concern

Comparison of BLS with Other Price Indexes for Microprocessors

Microprocessor Price Indexes

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f lamm hedonic

BLS PPI

FRB

Better Benchmarks for Semiconductor Innovation Tracking it better in a time of change

Focus more scarce stat resources on price indexes for IT sectors, reflecting growing relative importance to economy

A real collection program for underlying price data, perhaps coordinated with industry trade organizations

Under the hood at Dataquest (& others) not a pretty story

Decent coverage of products besides memory and microprocessors

New initiatives in communications Better understanding of R&D trends Better coordination of public/private R&D

investments