arm boards for dsp applications

M. S. Ramaiah School of Advanced Studies 1

M. Sc. (Engg.) in Electronics System Design

Engineering

GREESHMA SCWB0913004 , FT-2013

6th Module Presentation

Module code : ESE2511

Module name : Microcontrollers and Interfacing

Module leader : Mr. Nagananda S.N.

Presentation on : 07/05/2014

ARM Boards for DSP Applications


• INTRODUCTION

• ARM9E-S

• DM3730

• FUNCTIONAL BLOCK DIAGRAM

• BLOCK DIAGRAM

• SOFTWARE ARCHITECTURE

• CHARACTERISTICS OF DSP PROCESSORS

• FEATURES OF DM3730

• REPRESENTING A DIGITAL SIGNAL

• ADDITION AND SUBTRACTION OF FIXED-POINT SIGNAL

Overview


• MULTIPLICATION AND DIVISION OF FIXED-POINT SIGNAL

• SQUARE ROOT OF FIXED POINT SIGNAL

• DSP ON ARM9E

• DSP ON ARM10E

• FIR FILTER

• IIR FILTER

• THE DISCRETE AND FAST FOURIER TRANSFORM

• APPLICATIONS

• CONCLUSION

• REFERENCES

Overview


Introduction

Emerging standards for algorithms in many application areas have put further demands

on the ability of processing platforms to deliver efficient control capability

ARM’s approach has been to design RISC core architectures with instruction sets that

provide efficient support for particular applications, with optimal balance between

hardware and software implementation

To accelerate signal-processing algorithms ARM adds new DSP instructions to the

ARM instruction set

ARM DSP extensions broaden the suitability of the ARM CPU family to applications

that require intensive signal processing and at the same time retaining the power and

efficiency of a high performance RISC microcontroller

The ARM DSP extensions have already been implemented in the ARM926EJ-S,

ARM946E-S, ARM966E-S, ARM9E-S


Introduction

Processing digitalized signals requires high memory bandwidths and fast multiply

accumulate operations

A microcontroller handles the user interface, and a separate DSP processor manipulate

digitalized signals such as audio

A single-core design can reduce cost and power consumption over a two-core solution

The ARMv5TE extensions available in the ARM9E and later cores provide

efficient multiply accumulate operations

DSP applications are typically multiply and load-store intensive

Filtering is most commonly used signal processing operation

Another very common algorithm is the Discrete Fourier Transform


Introduction


ARM9E-S

The ARM9E-S core has the ARM architecture v5TE

This includes an enhanced multiplier design for improved DSP performance

It is a 32-bit microcontroller

It offers high performance for very low power consumption and gate count

The ARM architecture is based on Reduced Instruction Set Computer (RISC)

principles

The reduced instruction set and related decode mechanism are much simpler than

those of Complex Instruction Set Computer (CISC) designs

This simplicity gives

• a high instruction throughput

• an excellent real-time interrupt response

• a small, cost effective, processor macrocell


DM3730

Based on enhanced device architecture

Integrated on TI’s advanced 45-nm technology

Device supports HLOS and RTOS

Fully backward compatible


Functional Block Diagram

Figure 1 : DM3730 Functional Block Diagram


Block Diagram

Benefits

• 2000DMIPS for Oss like linux, Win CE,

RTOS

• 3-D graphics up to 20M polygons per

second for robust GUIs

• Backward compatible with OMAP3530

Figure 2 : DM3730 Block

Diagram

Application

• Smart connected devices

• Patient monitoring

• Media Player


Software Architecture

Figure 3 : Software Architecture of DM3730

Industry Standard OS component

TI provider component

Open Source


Characteristics of DSP processor

Harvard Architecture

High performance MAC

Saturating math

SIMD instruction for parallel computation

Barrel shifters

Floating point hardware


Features of DM3730

ARM microprocessor subsystem

Enhanced direct memory access controller

Video hardware accelerators

Tile based architecture delivering up to 20MPoly/sec

DSP instructions/data little Endian

NEON multimedia architecture

Load store architecture with Non-aligned support

64 32-Bit General purpose registers

Six ALUs, each supports single 32-bit, dual 16-bit, or quad-8 bit , Arithmetic per

clock cycle


Representing a Digital Signal

Figure 4 : Digitalizing an Analogue Signal

x is signal and t is time

In an analogue signal x[t ], the index t and the value x are both continuous real

variables

ARM uses fixed point representation


Addition and Subtraction of Fixed-Point Signals

The general case is to convert the signal equation

Fixed-point format

or in integer C

n = m = d. Therefore normal integer addition gives a fixed-point

Provided d = m or d = n


Contd…

There are four common ways you can prevent overflow

• Ensure that the X[t ] and C[t ] representations have one bit of spare headroom each

• Use a larger container type for Y than for X and C

• Use a smaller Q representation for y[t ]

• For example, if d = n − 1 = m − 1, then the operation becomes

• Use saturation


Multiplication of Fixed-Point Signals


Fixed point format

or in integer C

Division of Fixed-Point Signals


fixed point format

or in integer C


Square Root of a Fixed-Point Signals


Fixed point format

or in integer C


DSP on the ARM9E

The ARM9E core has a very fast pipelined multiplier array that performs a 32-bit by 16

-bit multiply in a single issue cycle

Writing DSP Code for the ARM9E

The ARMv5TE architecture multiply operations are capable of unpacking 16-bit halves

from 32-bit words and multiplying them

The multiply operations do not early terminate. Therefore use MUL and MLA for

multiplying 32-bit integers. For 16-bit values use SMULxy and SMLAxy

Multiply is the same speed as multiply accumulate. Use the SMLAxy instruction

rather than a separate multiply and add


DSP on the ARM10E

The ARM10E implements a background loading mechanism to accelerate load and store

multiples

It uses a 64-bit-wide data path that can transfer two registers on every background cycle

Writing DSP Code for the ARM10E

Load and store multiples run in the background to give a high memory bandwidth

Ensure data arrays are 64-bit aligned so that load and store multiple operations can

Transfer two words per cycle

The multiply operations do not early terminate. Therefore use MUL and MLA for

multiplying 32-bit integers. For 16-bit values use SMULxy and SMLAxy

The SMLAxy instruction takes one cycle more than SMULxy


FIR filters

The finite impulse response (FIR) filter is a basic

building block of many DSP applications

FIR filter to remove unwanted frequency ranges, boost

certain frequencies, or implement special effects

The FIR filter is the simplest type of digital filter

The filtered sample y(t) depends linearly on a fixed, finite number of unfiltered

samples x(t)

Calculating accumulated values A[t ]


IIR filters

An infinite impulse response (IIR) filter is a digital filter

that depends linearly on a finite number of input samples

and a finite number of previous filter outputs

Mathematically

Factorize the filter into a series of bi quads—an IIR filter with M = L = 2

Z-Transform


The Discrete Fourier Transform

The Fast Fourier Transform

The Discrete Fourier Transform (DFT) converts a time domain signal to a

frequency domain signal

A FFT is an algorithm to compute the discrete Fourier transform and its inverse


Applications

Portable data terminals

Navigation

Auto Infotainment

Gaming

Medical Imaging

Home automation

Single board


Conclusion

DM3730 cost effective

It is low power and has high performance

DM3730 delivers a nearly 40% increase in ARM performance

Over 50% increase in DSP performance

Has twice the graphics capability, while reducing power consumption

Use a fixed-point representation for DSP applications where speed is critical with

moderate dynamic range


Reference

1. DM3730, http:// www.ti.com/lit/ds/symlink/dm3730.pdf

2. DM3730, http://www.ti.com/lit/ml/sprt571/sprt571.pdf

3. DM3730, http://media.digikey.com/pdf/ DM3730_AM3703TorpedoSOMBrief.pdf

arm boards for dsp applications

Documents

tis advanced

reduced instruction

complex instruction

arm architecture v5tethis

analogue signal xt

signal equationfixed

nagananda s

analogue signalxis signal