DYNAMICALLY RECONFIGURABLE SYSTOLIC ARRAY ACCELERATORS:A CASE STUDY WITH EKF AND DWT ALGORITHMS

Robert BarnesUtah State UniversityDepartment of Electrical and Computer EngineeringThesis Defense, November 13th 2008

Outline

Introduction & Background System Design Results & Conclusions

Motivation

Increasing Demands for Spacecraft Low Power

Fault Tolerant

Flexibility

High Performance Solution: FPGA

General Goals

Flexible Extended Kalman Filter (EKF) System on an FPGA Adaptable to changing performance

requirements (scalable). System adaptable to other algorithms (DWT).

Outperform RAD750 PowerPC

Explore applications of dynamic reconfiguration.

Kalman Filter

To navigate in space an autonomous spacecraft must accurately estimate its state from noisy measurements.

The filter is very flexible Estimate a system’s state from only a single

sensor Estimate the bias in sensors Determine an unknown system model Predict a future states

Faddeev Algorithm

Extended Kalman Filter

Discrete Wavelet Transform Algorithm

Systolic Arrays

A network of simple processing elements (PE) which rhythmically process and pass data to nearest neighbours to process larger complex tasks.

Features: Modularity Regularity Locality Synchronous Pipelined Data Reuse

Partial Dynamic Reconfiguration

Configuration Layout

Figure Source: Jeff Carver

Other Reconfiguration Methods

JBits Interface to make changes to the Bitstream

Modular Design Flow Early Access Design Flow

Improved Modular Design Flow

Scaling Methods

Soft scaling Using conditional variable loops and conditional

statements, software can easily be made to scale to different parameters.

Static Hardware Scaling Using MUXes a hardware architecture can be

designed where data can be re-routed to different hardware cores.

Reconfigurable Hardware Scaling Using partial dynamic reconfiguration the physical

size of the systolic array can be scaled.

Outline

Introduction & Background System Design Results & Conclusions

PolySAF

Polymorphic Systolic Array Framework (PolySAF)

Co-Processor

SwitchBox

Interface Hierarchy

2D Fadeev Systolic Array

Vertical Systolic Array

Hardware/Software Mapping

DWT Systolic Array

Hybrid PDR

Mapping & Scaling

Outline

Introduction & Background System Design Results & Conclusions

Floor Planning

Floor Planning Sockets

Sockets vs Problem Size vs Cycles

Comparison with PowerPC

Reconfiguration Performance

Area Analysis

Conclusions & Limitations

A polymorphic systolic array framework (PolySAF). Programmable switchboxes and protocol to allow dynamic scaling in the

array. Efficient EKF and DWT accelerators

Speedup of at least 4.18x and 6.61x over PowerPC for EKF and DWT. Integration of bitstream relocation and bitstream compression into a

practical system. 2.7x improvement in reconfiguration time.

A 44% improvement in BRAM usage.

The flexible and simple framework allows this design to host a broad range

of algorithms.

Dynamic reconfiguration is powerful, but it is not useful in every application.

The trade-offs must be weighed carefully.

Questions?

Publications

R. Barnes and A. Dasu, “Hardware/software Co-designed Extended Kalman Flter on an FPGA,” in The International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA), 2008.

R. Barnes, A. Dasu, J. Carver, and R. Kallam, “Dynamically Reconfigurable Systolic Array Accelerators: A case study with EKF and DWT Algorithms,” Institution of Engineering and Technology (IET) Computers & Digital Techniques. In Review.

Misc.

Hours: 4.33wks/month*16months*(>40hours/wk)

= ~2771hours

Embedded C: ~6,000

Verilog Code: ~3,222

Python: ~1015

Tools: EDK ISE Modelsim MatLab Xpower PlanAhead Eclipse Simics Python