using a csp based programming model for reconfigurable processor arrays

Using a CSP based Programming Model for

Reconfigurable Processor ArraysBy: [email protected]

"Using a CSP based Programming Model for Reconfigurable Processor Arrays", Zain-ul-Abdin 2

Motivation• Emergence of new heterogeneous parallel

architectures– Increased Performance– Power Efficiency

• Traditional methods– Automatic parallelization by compilers– Use of Thread model of computation

• Highly non-deterministic

• Use of Concurrent Programming Model– Expresses computations in a productive manner by

matching it to target hardware– Supported by a compiler for allowing portability


Array of Processors

• Consists of heterogenous processors with specialized interconnection netrworks

• Improved performance by exploiting paralellism rather than scaling clock frequency

• Flexible due to dynamically reconfigurable interconnection network

• Energy Efficient– Individual brics can be switched off when not in use– The Clock frequency of brics can be optimized


Ambric Programming Model

• Design consists of:– Objects: defines the

functionality in either java subset or assembly.

– Structured composition described in aStruct


Ambric-Simple ExampleDesign Toplevel

design SimpleDesigntop { Root_IF root_Inst;}

interface Root_IF {}

binding CompRoot implements Root_IF {

simpledesign process1;

Vio inOut = {NumSources = 1, NumSinks = 1};

channel c0 = {inOut.out[0], process1.in};channel c1 = {process1.out, inOut.in[0]};}

Object Structure

interface simpledesign {

inbound in;

outbound out;

}

binding Javasimpledesign implements simpledesign {

implementation "simpledesign.java";

}

Object Implementation

import ajava.io.InputStream;

import ajava.io.OutputStream;

public class simpledesign {

public void run(InputStream<Integer> in, OutputStream<Integer> out) {

while (true) {

out.writeInt(in.readInt());

}

}

}


Why use Occam-pi?

• Language level support for concurrency

• Provides higher order combinators for facilitating composition of re-targetable data parallel descriptions

• Sematically transparent PAR/SEQ style• Explicit control of graularity of parallelism

and data locality


Occam-pi Language

• Based on ideas of CSP with pi-calculus

• Abstractions for underlying hardware– Processes– Channels (Unbuffered message passing)

• Rendezvous behavior of channels– Receiver blocks until the sender wrote the value – Sender continues after the receiver read the value


Occam-pi Language

• Primitive actions– Variable assignment– Channel output !– Channel input ?– PAR– SEQ

• Variables can only be written by one process in parallel– Likewise, only a single process can read from a channel, and

another single process can write to the channel

PROC SimpleEx() INT x,y:

CHAN OF INT c,d:PAR SEQ

c ! 117d ? x

SEQc ? yd ! 118

:


Compilation Methodology

• Implemented a Backend for Ambric in Tock(Translator of Occam to C by Kent)

• Staged compilation

• Native SOPL code generation for Ambric– Use of concurrency of Occam-pi– Reduced memory footprint


Occam-Ambric Compilation


Ambric-related Transformations

• Introduction of Channel-end Specifiers• Enables use of flat data parallelism• Replicators transformations:

– SEQ Replicators to For loops– PAR Replicators unrolled to multiple PROCs

• Emission of aStruct structural interface and binding code for each PROC

• Emission of aJava class code corresponding to each PROC


1D-Discrete Cosine Transform


Performance Results

• 8-point DCT Implementations

NP CLFO Throughput

Serial DCT 1 220 TS

Coarse-grained Parallelized DCT

4 51 3TS

Fine-grained Parallelized DCT

34 33 27TS


Conclusions

• Proposed the use of Occam-pi for programming a coarse-grained processor architecture

• Raises the abstraction level while not compromising the efficiency

• To extend the compiler for supporting mobility features of Occam-pi for reconfigurable logic

using a csp based programming model for reconfigurable processor arrays

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