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Презентация на тему Parallel Architecture Intro

More Logistics Projects: simulation-based, creative, be prepared to spend time towards end of semester – more details on simulators in a few weeks Grading: 50% project 20% multi-thread programming assignments 10% paper critiques 20% take-home final
Lecture 1: Parallel Architecture Intro Course organization: ~5 lectures based on Culler-Singh More Logistics Projects: simulation-based, creative, be prepared to spend time towards end Parallel Architecture TrendsSource: Mark Hill, Ravi Rajwar CMP/SMT Papers CMP/SMT/Multiprocessor papers in recent conferences: Bottomline Can’t escape multi-cores today: it is the baseline architecture Performance stagnates Symmetric Multiprocessors (SMP) A collection of processors, a collection of memory: both Distributed Memory Multiprocessors Each processor has local memory that is accessible through Shared Memory Architectures Key differentiating feature: the address space is shared, i.e., Shared Address SpaceSharedPrivatePrivatePrivateProcess P1Process P2Process P3SharedSharedSharedPvt P1Pvt P2Pvt P3Virtual address spaceof each processPhysical address space Message Passing Programming model that can apply to clusters of workstations, SMPs, Models for SEND and RECEIVE Synchronous: SEND returns control back to the Deterministic Execution Need synch after every anti-diagonal Potential load imbalance Shared-memory vs. Cache CoherenceA multiprocessor system is cache coherent if a value written by Cache Coherence Protocols Directory-based: A single location (directory) keeps track of the Title Bullet
Слайды презентации

Слайд 2 More Logistics
Projects: simulation-based, creative, be prepared to

More Logistics Projects: simulation-based, creative, be prepared to spend time towards

spend time towards end of semester – more details

on
simulators in a few weeks

Grading:
50% project
20% multi-thread programming assignments
10% paper critiques
20% take-home final

Слайд 3 Parallel Architecture Trends
Source: Mark Hill, Ravi Rajwar

Parallel Architecture TrendsSource: Mark Hill, Ravi Rajwar

Слайд 4 CMP/SMT Papers
CMP/SMT/Multiprocessor papers in recent conferences:

CMP/SMT Papers CMP/SMT/Multiprocessor papers in recent conferences:    2001

2001 2002

2003 2004 2005 2006 2007

ISCA: 3 5 8 6 14 17 19

HPCA: 4 6 7 3 11 13 14

Слайд 5 Bottomline
Can’t escape multi-cores today: it is the

Bottomline Can’t escape multi-cores today: it is the baseline architecture Performance

baseline
architecture

Performance stagnates unless we learn to transform

traditional applications into parallel threads

It’s all about the data!
Data management: distribution, coherence, consistency

It’s also about the programming model: onus on
application writer / compiler / hardware

It’s also about managing on-chip communication

Слайд 6 Symmetric Multiprocessors (SMP)
A collection of processors, a

Symmetric Multiprocessors (SMP) A collection of processors, a collection of memory:

collection of memory: both
are connected through some interconnect

(usually, the
fastest possible)

Symmetric because latency for any processor to access
any memory is constant – uniform memory access (UMA)

Proc 1

Proc 2

Proc 3

Proc 4

Mem 1

Mem 2

Mem 3

Mem 4


Слайд 7 Distributed Memory Multiprocessors
Each processor has local memory

Distributed Memory Multiprocessors Each processor has local memory that is accessible

that is accessible
through a fast interconnect

The different

nodes are connected as I/O devices with
(potentially) slower interconnect

Local memory access is a lot faster than remote memory
– non-uniform memory access (NUMA)

Advantage: can be built with commodity processors and
many applications will perform well thanks to locality

Proc 1

Mem 1

Proc 2

Mem 2

Proc 3

Mem 3

Proc 4

Mem 4


Слайд 8 Shared Memory Architectures
Key differentiating feature: the address

Shared Memory Architectures Key differentiating feature: the address space is shared,

space is shared,
i.e., any processor can directly address

any memory
location and access them with load/store instructions

Cooperation is similar to a bulletin board – a processor
writes to a location and that location is visible to reads
by other threads

Слайд 9 Shared Address Space
Shared
Private
Private
Private
Process P1
Process P2
Process P3
Shared
Shared
Shared
Pvt P1
Pvt P2
Pvt

Shared Address SpaceSharedPrivatePrivatePrivateProcess P1Process P2Process P3SharedSharedSharedPvt P1Pvt P2Pvt P3Virtual address spaceof each processPhysical address space

P3
Virtual address space
of each process
Physical address space


Слайд 10 Message Passing
Programming model that can apply to

Message Passing Programming model that can apply to clusters of workstations,

clusters of workstations, SMPs,
and even a uniprocessor

Sends

and receives are used for effecting the data transfer – usually,
each process ends up making a copy of data that is relevant to it

Each process can only name local addresses, other processes, and
a tag to help distinguish between multiple messages

A send-receive match is a synchronization event – hence, we no
longer need locks or barriers to co-ordinate

Слайд 11 Models for SEND and RECEIVE
Synchronous: SEND returns

Models for SEND and RECEIVE Synchronous: SEND returns control back to

control back to the program
only when the RECEIVE

has completed

Blocking Asynchronous: SEND returns control back to the
program after the OS has copied the message into its space
-- the program can now modify the sent data structure

Nonblocking Asynchronous: SEND and RECEIVE return
control immediately – the message will get copied at some
point, so the process must overlap some other computation
with the communication – other primitives are used to
probe if the communication has finished or not

Слайд 12 Deterministic Execution















Need synch after every anti-diagonal
Potential

Deterministic Execution Need synch after every anti-diagonal Potential load imbalance Shared-memory

load imbalance
Shared-memory vs. message passing
Function of

the model for SEND-RECEIVE
Function of the algorithm: diagonal, red-black ordering











Слайд 13 Cache Coherence
A multiprocessor system is cache coherent if

Cache CoherenceA multiprocessor system is cache coherent if a value written

a value written by a processor is eventually visible

to
reads by other processors – write propagation

two writes to the same location by two processors are
seen in the same order by all processors – write
serialization

Слайд 14 Cache Coherence Protocols
Directory-based: A single location (directory)

Cache Coherence Protocols Directory-based: A single location (directory) keeps track of

keeps track
of the sharing status of a block

of memory

Snooping: Every cache block is accompanied by the sharing
status of that block – all cache controllers monitor the
shared bus so they can update the sharing status of the
block, if necessary

Write-invalidate: a processor gains exclusive access of
a block before writing by invalidating all other copies
Write-update: when a processor writes, it updates other
shared copies of that block

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