Download pdf - Department of Electrical and Computer Engineering Computer ... · Department of Electrical and Computer Engineering Computer Architecture and Parallel ... Advanced Topics in ... (1994),

Department of Electrical and Computer Engineering Computer Architecture and Parallel Systems Laboratory - CAPSL

Guang R. Gao ACM Fellow and IEEE Fellow

Endowed Distinguished Professor

Electrical & Computer Engineering

University of Delaware

[email protected]

Topic A – Part 3 Dataflow Model of Computation

(From Dataflow to Multithreading)

Topic-Gao-Dataflow-part3 1 3/21/2014

CPEG 852 - Spring 2014

Advanced Topics in Computing

Systems

CPEG852-Spring14: Topic A - Dataflow - 1 2

Evolution of Multithreaded Execution and Architecture Models

Non-dataflow based

CDC 6600 1964

MASA Halstead 1986

HEP B. Smith 1978

Cosmic Cube Seiltz 1985

J-Machine Dally 1988-93

M-Machine Dally 1994-98

Dataflow model inspired

MIT TTDA Arvind 1980

Manchester Gurd & Watson 1982

*T/Start-NG MIT/Motorola 1991-

SIGMA-I Shimada 1988

Monsoon Papadopoulos & Culler 1988

P-RISC Nikhil & Arvind 1989

EM-5/4/X RWC-1 1992-97

Iannuci’s 1988-92

Others: Multiscalar (1994), SMT (1995), etc.

Flynn’s Processor 1969

CHoPP’77 CHoPP’87

TAM Culler 1990

Tera B. Smith 1990-

Alwife Agarwal 1989-96

Cilk Leiserson

LAU Syre 1976

Eldorado

CASCADE

Static Dataflow Dennis 1972 MIT

Arg-Fetching Dataflow DennisGao

1987-88

MDFA Gao

1989-93

EARTH Hum et al. 1993-2006

HTVM/TNT-X DelCuvillo and Gao

2000-2010

Codelet Model

Gao et. al. 2009-

A version of this slide was presented

in my invited talk at Fran Allen’s

retirement party July 2002

3/21/2014 3 Topic-Gao-Dataflow-part3

A Multithreaded Architecture

To Other PE’s

One PE


Case Studies – Dataflow Model Insired Multithreading

• McGill Dataflow Model (1988 - 1993)

• EARTH Model (1993 – mid 2000s )

• The UHPC/Runnemede Model (2010 - )


McGill Data Flow Architecture Model

(MDFA)


n1

n2 n3

fetch fetch

n1

n2 n3

store

fetch fetch

Argument –flow Principle Argument –fetching Principle


A Dataflow Program Tuple

Program Tuple = { P-Code . S-Code }

P-Code

N1: x = a + b;

N2: y = c – d;

N3: z = x * y;

S-Code

2

3 n1

a

b

2

3 n2

c

d

2

3 n3

IPU ISU


The McGill Dataflow Architecture Model

Pipelined Instruction

Processing Unit (PIPU)

Dataflow Instruction

Scheduling Unit (DISU)

Enable Memory &

Controller

Signal

Processing

Fire Done


The McGill Dataflow Architecture Model





Fire Done

Waiting Instructions

Enabled Instructions = PC

Important Features

Pipeline can be kept fully

utilized provided that the

program has sufficient

parallelism


The Scheduling Memory (Enable)



C

O

N

T

R

O

L

L

E

R

1 1

1 1

0 1

0 0

0 0

0

1 1

1

1 0

0 0

0 1

Signal Processing

Fire Done

Count Signal(s)

0 Waiting Instructions 1 Enabled Instructions


Advantages of the McGill Dataflow Architecture Model

• Eliminate unnecessary token copying and transmission overhead.

• Instruction scheduling is separated from the main datapath of the processor (e.g. asynchronous, decoupled).


Von Neumann Threads as Macro Dataflow Nodes

1

2

3

k

A sequence of

instructions is “packed”

into a macro-dataflow

node

Synchronization is done

at the macro-node level


The Von Neumann-type Processing

begin for i = 1 … … endfor end

Source Code

Compiler Sequential

Machine

Representation

CPU

Load

Processor


Hybrid Evaluation Von Neumann Style Instruction Execution” on

the McGill Dataflow Architecture • Group a “sequence” of dataflow instruction into a “thread” or

a macro dataflow node. • Data-driven synchronization among threads. • “Von Neumann style sequencing” within a thread. Advantage: Preserves the parallelism among threads but avoids

unnecessary fine-grain synchronization between instructions within a sequential thread.


What Do We Get?

• A hybrid architecture model without sacrificing the advantage of fine-grain parallelism!

(latency-hiding, pipelining support)


A Realization of the Hybrid Evaluation





Fire Done

Shortcut

1 2 k

Von Neumann bit


Case Studies – Dataflow Model Inspired Multithreading

• McGill Dataflow Model (1988 - 1993)

• EARTH Model (1993 – mid 2000s )

• The UHPC/Runnemede Model (2010 - )


CPU

Memory

Fine-Grain non-preemptive thread-

The “hotel” model

Thread

Unit

Executor

Locus

Coarse-Grain vs. Fine-Grain Multithreading

A Pool

Thread

CPU

Memory

Executor

Locus

A Single

Thread

Coarse-Grain thread-

The family home model

Thread

Unit

[Gao: invited talk at Fran Allen’s Retirement Workshop, 07/2002]