isca needle a 0610

8/4/2019 Isca Needle a 0610

1/64

Moving the NeedleComputer Architecture Research

in Academe and Industry

Bill DallyChief Scientist & Sr. VP of Research, NVIDIABell Professor of Engineering, Stanford University


2/64

Outline

The Research Funnel

Most ideas fail

Those that succeed take 5-10 years

The Research FormulaConstraints

The Academic Advantage

The Industrial Advantage

StartupsBest practices


3/64

Goal Positive Impact on a Product


4/64

T

he Research Funnel

Applications

Technology

Concept

DevModel Eval Dev

insight


5/64

Most ideas fail

The ideas that succeed take a long time

Concept

DevModel Eval Dev


6/64

Most ideas fail


Concept

DevModel Eval Dev


7/64

Most ideas fail

So terminate the bad ones quickly


8/64

Most ideas fail

So terminate the bad ones quickly

Be a terminator, not an advocate


9/64

Dally, Micro-Optimization of Floating-Point Operations, ASPLOS, 1989, pp 283-289


10/64


11/64

Most ideas fail


Concept

DevModel Eval Dev


12/64


So aim research 5-10 years ahead ofcurrent practice


13/64

Current Architecture Practice


14/64


15/64

Aim Here


16/64

Enable this point


17/64

Timeline for some ideas

Idea Concept Published Product (T

Stream Processing 1995 1998 2006 11

Virtual Channels 1985 1990 1992 7

Equalized Signaling 1995 1996 2000 5

High-Radix Networks 2002 2005 2008 6


18/64

The Performance Equation

ckfCPINITime v!


19/64

The Research Formula

ROI! rewardriskv effort


20/64

Reward

If you are wildly successful, whatdifference will it make?

ROI!reward

riskv effort


21/64

Effort

Learn as much as possible with as littlework as possible

ROI!reward

riskv effort


22/64

Effort

Do the minimum analysis andexperimentation necessary to make apoint

ROI!reward

riskv effort


23/64

Real and Artificial Constraints

Real Constraints Artificial Constraints

Laws of physicsFuture semiconductor processes

Packaging and thermal limitsFuture applications

Existing ISAExisting OST

odays benchmarksExisting compilersInfrastructure


24/64

Constraining Infrastructure

uArch

Idea

Other

uArch

ISA

Compiler

Benchmarks

Binaries

Simulator


25/64


uArch

Idea

Other

uArch

ISA

Compiler

Benchmarks

Binaries

Simulator


26/64


uArch

Idea

Other

uArch

ISA

Compiler

Benchmarks

Binaries

Simulator


27/64

The contribution is insight

Not novelty

Not numbers


28/64

Research is ahunt for insight

Need to get off the beatenpath to find new insights


29/64

Road-Kill Research

uArch

Idea

Other

uArch

ISA

Compiler

Benchmarks

Binaries

Simulator


30/64


31/64

Looking here for lost keys


32/64

Lost keys here

Looking here


33/64



34/64


Freedom


35/64


Freedom from artificial constraints

Freedom to fail (take risks)


36/64

Academic research matched for earlystages of the funnel

Concept

DevModel Eval Dev


37/64

Example: ELM


38/64

Example: ELM

Balfour et al., "An Energy-Efficient Processor Architecture for Embedded Systems"CAL, Jan. 2008, pp 29-32.


39/64

ELM Infrastructure

uArch

Idea

Other

uArch

ISA

Compiler

Benchmarks

Binaries

Simulator

Changed for ELM


40/64


Resources and Experience


41/64


Resources to carry out detailed studies

Experience to address commercial

constraints


42/64

The ideal partnership:

Academic research 5-10 years out,focused on industry problems

Transferinsightto industrial researchto refine into product

Concept

DevModel Eval Dev


43/64

What transfers is insight

Not academic design

Not performance numbers


44/64

What transfers is insight

And its transferred by people

Not papers


45/64

Concept

Analysis

Simulation

Prototype

Refine Concept

Detailed Design

Academic

Industrial


46/64


47/64

Example: Cray T3D and T3E


48/64

J-Machine

MIT 1987-1992 3-D network

Global address space Fast messaging andsynchronization

Support for manymodels of computation


49/64

Cray T3D

Started working with Cray in1989

Project started early 1990 First ship in mid 1992

From J-Machine Network Fast communication/sync Global address space

For reality Alpha processors MECL gate arrays Robust software stack


50/64

Best Practices for Academics

Long-term perspective (5-10 years) Know your customer and their long-term issues Look at tomorrows applications, not yesterdays

Maximize reward, minimize effort Estimate maximum impact terminate Minimal analysis and experiment to make the point

Exploit your freedom

Dont be limited by exiting tools, benchmarks, ISAs, Carry result to impact Build relationships with industry

ROI! rewardriskv effort

uArchIdea

ther

ISA

Compiler

Benchmarks

Binaries

Simulator


51/64

Best Practices for Industry

Leverage academic research Build partnerships Articulate long-term research issues Be open-minded

Minimize artificial constraints Carry concepts across the gap Open infrastructure


52/64

A Partnership

Academe Industry

Filtered, De-risked Concepts

Future issuesInfrastructure


53/64

The Startup Path

When you cant find an appropriateindustrial partner, make one.

STAC, Avici, Velio, SPI


54/64

Concept

Analysis

Simulation

Prototype

Refine Concept

Detailed Design

Academic

Startup


55/64

Startup Pros/Cons

Pros

Dont have to convinceexisting company to

change course (until exit)

Cons

Have to convince investors(repeatedly)

Have to build a whole company,not just a development team Finance, sales, marketing,

Limited resources Impatient capital


56/64

Example: SPI

Date Event

Jan 2004 SPI Incorporated

Nov 2004 First round financing

April 2006 Tapeout Storm-1Oct 2006 First ship of Storm-1

2007 Software, software, software

2008 Customers in production

Sept 2009 Doors close


57/64

Much easier to license technology toan existing company


58/64

Starting a company to bring a newsemiconductor product to market costs$30M (to cash flow positive)

If its a programmable processor, its $70M

Investors want a 10x ROI

Need to see a $700M exit to justify a newprocessor company


59/64

The future of computer architecture


60/64

The future of computer architecture

NOW is an ideal time for research to move the needle Computers are drastically changing Pervasive parallelism

Energy limited Bandwidth constrained

Opportunity to set the MSB of future computers in thenext few years

Requires changing the whole stack Requires industry-academe partnership


61/64

Energy-Efficient Architecture

Abstracting Locality

20mm

7pJ

50pJ 500pJ

2000pJ

2000pJ

P P P P

L1 L1 L1 L1Net

L2

Net

L3


62/64

Solution involves many levels of the stack

Application

Algorithm

Prog. System

Compiler

ISA

uArch

Design

Circuits

Process

Too constrained toinnovate within one layer


63/64

Industry

Academe

ROI!reward

riskv effort

uArch

Idea

Other

uArch

ISA

Compiler

Benchmarks

Binaries

Simulator


64/64

Moving the Needle

Computer Architecture Research

in Academe and Industry

Bill DallyChief Scientist & Sr. VP of Research, NVIDIABell Professor of Engineering, Stanford University

isca needle a 0610

Documents