Survey of multicore architectures

Marko BertognaScuola Superiore S.Anna,

ReTiS Lab, Pisa, Italy

Summary

CELL processor Reconfigurable devices Software-Hardware co-design Parallel programming problems

data dependencies process synchronization memory barriers locking mechanisms

Language extensions for parallel programming

Real-time multiprocessor scheduling

Cell processor

A Cell Processor

Cell History

Cell basic concepts

Cell synergy

Cell Chip

Cell features

Cell Processor Components

Cell Processor Components

Cell Processor Components

Cell Processor Components

Synergistic Processor Element (SPE)

SPE

SPE details

Element Interconnect Bus (EIB)

EIB: Data topology

Example: 8 concurrent transactions

Theoretical peak operations

Cell BE performance

Why is Cell Processor so fast?

CELL software environment

System Level Simulator

SPE management library

CELL parallelism

Typical CELL sw development flow

ARM’s MPcore

PicoArray (by PicoChip)

PicoArray scaling

FPGA and Reconfigurable devices

Field Programmable Gate Arrays

SRAM-based matrix of integrated elements whose interconnections can be programmed statically or even dynamically

Basic block is Logic Element (LE) Chip capacities from 1k to 1000k LEs Each LE is typically composed by logic

gates, LUTs, Flip-Flops and latches Need for optimized CAD or pre-binded

design libraries

FPGA

CSL organization: Basic Logic Element:

Altera’s Stratix IV basic block Adaptive Logic Module (ALM)

Flexibility vs efficiency

Reconfigurable devices advantages

Efficiency AND Flexibility Time to market Easier upgrade Lower cost (on scale production) Reusable IP Customable interface

Reconfigurable devices parameters

Block granularity Coarse grained: Functional Units, Processor

Cores, Memory Tiles Fin grained: gate and register level

Density Reconfiguration time

Compile-Time Reconfiguration (CTR) Run-Time Reconfiguration (RTR)

Partial or Total reprogramming

Triscend’s A7S chip

Example: multiplier on Altera’s Stratix IV

Typical FPGA software development environment

FPGA optimized module library

IO Editor Generate file.h Bind (placement and

route) file.csl Config file.cfg Download

Typical FPGA module library

Altera’s Nios II

Nios II is a soft-core processor IP that can be downloaded into an Altera’s

FPGA, obtaining the functionalities of a real RISC CPU

Logic elements are programmed so as to behave like gates of classic ASIC processors

Different Nios versions are available faster and with full functionalities bigger size medium sized compact but slower and with limited

functionalities

Nios II core

Selecting Nios II e/s/f

Example of a Nios II Processor system

Final global layout

Soft-core processors and FPGAs

Possible to have multiple cores on a single chip

Customizable hardware can be used to coordinate the various cores

Build and test a whole multicore system in a faster time

Detect and solve bottlenecks without needing to repeatedly return to the integration phase

Co-design problems with FPGAs

A task may be executed by a (soft-core or ASIC) processor or may be entirely implemented in hardware on the reconfigurable logic

“Programming in Space” versus “Programming in Time”

Centralized vs Distributed computing Sequential vs Parallel programming Interconnect Network

What is a task in hardware?

Software programming

c=a+b;

result=c/2;

Hardware implementation

a

b

c+

shifter

result

Assembler expansion:ldr r0,aldr r1,badd r0,r0,r1mov r0,LSR r0str r0,result

5 operations

All in one clock cycle!

Conclusions

FPGAs are interesting devices for multicore systems developers

Valid benchmark upon which to compare classic serial programming methods and parallel computing approaches

Allow reducing time-to-market for next-generation multicore systems

Provide common platforms that can easily reproduce any architecture (given a proper VHDL/Verilog description)