Concurrent Aggregates (CA) Andrew A. Chien and William J. Dally Presented by: John Lynn and Ryan Wu.

Concurrent Aggregates (CA)

Andrew A. Chien and William J. Dally

Presented by: John Lynn and Ryan Wu

Outline Motivation Serializing abstraction and concurrent

aggregates Features Programming with CA Discussion

Motivation Parallel programs to take advantage of the

massive hardware concurrency Two major concerns at that time:

Programming should be relatively easy (the complexity of writing object oriented languages)

Language must allow to express sufficient concurrency

Hierarchies of abstractions are used to manage complexity by serializing the abstractions, which may cause significant loss of concurrency

Serializing Abstractions Each object accepts one msg a

time Hierarchical abstractions

(abstractions built from other abstractions) are built from single objects

Most concurrent object-oriented languages serialize hierarchical abstractions

This leaves programmers with the choice of reduced concurrency or working without useful levels of abstraction

Concurrent Aggregates

Concurrent aggregates allow programmers to build hierarchical abstractions without serialization.

Each aggregate is multi-access to receive many messages simultaneously

Result: Increased message rate for lower levels

Background J-machine: 105 nodes, 64K words local

memory, fast communication Fine grain computation: msg passing,

context switching and fast task creation and dispatch

No shared memory, and each of the nodes executes instructions from local mem.

Concurrency in CA is derived from asynchronous messages sends and synchronization through context futures

Similar settings in sensor networks?

Four important features Intra-aggregate Addressing:

allows representatives of an aggregate to compute the names of other parts of the aggregate

Delegation: to piece together one aggregate’s

behavior from the behavior of others

First Class Messages: Allow programmers to write

message manipulation abstractions First Class Continuations:

enables programs to code synchronizing abstractions such as futures

Combining Tree Message form:

Combine <combiningtree> <selector> <value> <index>

Programming with Concurrent Aggregates: Syntax

Aggregate(aggregate <aggname> instance-variable* (parameters param-name+)(initial <aggsize> exp+))

Class (class <cname> instance-variable* (parameters

param-name+)(initial exp+))

(global <gname> initial-exp)

Example of Aggregate

(aggregate counter count

(parameters number_reps icount)

(initial number_reps)(forall index from 1 below number_reps

(set_count (sibling group index) icount))

(set_count self icount)))

Method and handler Handler

(handler <aggname> <messagename> (arg*) exp+)

Method (method <cname> <messagename> (arg*)

exp+) Delegate

(delegate <agg-or-cname> <messagename> instance-variable)

Control constructs and message sends

Aggregation and Naming Aggregate:

Homogeneous collection of objects (representatives) which are grouped together and may be referenced by a single aggregate name

Messages sent to the aggregate are directed to arbitrary representatives

(sibling group <index>)

Example

Delegation and Message Handling

Handlers are methods for aggregates

Delegates specify targets to handle messages

:rest delegate can handle messages with no specified handler

Bank Example Bank aggregate composed of tellers

aggregate, loan officer, and manager Unusual manages delegated to manager

Message Handling

Messages are first class objects in CA Can be created and modified programmatically Messages are passed by-value but copying is

only one level deep

Continuations What is a continuation? Separates code from

synchronization Futures as continuations

Futures Value method

returns value immediately if available, otherwise adds continuation to a list

Set_value method forwards value to all continuations on deferred list

Objects as Continuations A continuation is just an object

that expects a reply Complex synchronization

structures can be implemented as continuations

Barrier Barrier object

implements reply method

Once, maxcount is reached, all computations are resumed

Conclusion CA provides a programming

abstraction for dealing with many processors

Abstraction takes much of the complexity out of parallelizing a computation

First class continuations allow for modular synchronization structures

Discussion How might these concepts parallel

what we are trying to accomplish with sensor networks?

How do these concepts differ? Of what use could concurrent

aggregates be in programming a sensor network?