2. EC6703 EMBEDDED AND REAL TIME SYSTEMS

3. UNIT V CASE STUDY Data compressor Alarm Clock Audio player
Software modem
Digital still camera
Telephone answering machine
Engine control unit
Video accelerator.

4. ALARM CLOCK

5. Alarm clock interface Alarm on Alarm off buzzer PM Alarm ready light
set
time
set
alarm
hour
minute
button

6. Operations Set time: hold set time, depress hour, minute.
Set alarm time: hold set alarm, depress hour, minute.
Turn alarm on/off: depress alarm on/off.

7. Alarm clock requirements

8. Alarm clock class diagram1 1 1 1
Lights*
Display
Mechanism 1 1 1
Buttons*
Speaker* 1

9. Alarm clock physical classes
Lights*
Buttons*
Speaker*
digit-val()
digit-scan()
alarm-on-light()
PM-light()
set-time(): boolean
set-alarm(): boolean
alarm-on(): boolean
alarm-off(): boolean
minute(): boolean
hour(): boolean
buzz()

10. Display class Display time[4]: integer alarm-indicator: boolean
PM-indicator: boolean
set-time()
alarm-light-on()
alarm-light-off()
PM-light-on()
PM-light-off()

11. Mechanism class Mechanism Seconds: integer PM: boolean
tens-hours, ones-hours: boolean
tens-minutes, ones-minutes: boolean
alarm-ready: boolean
alarm-tens-hours, alarm-ones-hours:
boolean
alarm-tens-minutes, alarm-ones-minutes:
scan-keyboard()
update-time()

12. Update-time behavior update seconds with rollover
display.set-time(current time) F
Time >= alarm and alarm-on?
Rollover? F T T
update hh:mm
with rollover
alarm.buzzer(true)
PM->AM
AM->PM
PM=true
PM=false

13. Scan-keyboard behavior
Set-time and
not set-alarm
and hours
compute button activations
Alarm-on
Increment time
tens w. rollover
and AM/PM
alarm-ready=
true
Alarm-off
alarm-ready=
false
alarm.buzzer(false)
Increment time
ones w. rollover
and AM/PM
save button
states
Set-time and
not set-alarm
and minutes

14. System architecture Includes: Two major software components:
periodic behavior (clock);
aperiodic behavior (buttons, buzzer activation).
Two major software components:
interrupt-driven routine updates time;
foreground program deals with buttons, commands.

15. Interrupt-driven routine
Timer probably can’t handle one-minute interrupt interval.
Use software variable to convert interrupt frequency to seconds.

16. Foreground program Operates as while loop: while (TRUE) {
read_buttons(button_values);
process_command(button_values);
check_alarm(); }

17. Testing Component testing: System testing:
test interrupt code on the platform;
can test foreground program using a mock-up.
System testing:
relatively few components to integrate;
check clock accuracy;
check recognition of buttons, buzzer, etc.

19. Audio players
Audio players may use flash, hard disk, or CD for mass storage.
An MP3 player performs three basic functions: audio storage, audio decompression,and user interface.
Decompression requires small amount of CPU:
10% of ARM7.
File system must be compatible (FAT).
Cirrus CS7410

20. Digital still cameras
DSC must determine exposure before taking picture.
After taking picture:
Improve image quality.
Compress.
Save as file.

21. Digital still camera architecture
DSC uses CPU for general-purpose processing, DSP for image processing.
Internal memory buffers the passes on the image.
Display is lower resolution than image sensor.
Image must be down sampled.

22. Image capture Before taking picture: Determine exposure.
Determine focus.
Optimize white balance.
Bayer pattern

23. Image processing Must perform basic processing to get usable picture:
Bayer->RGB interpolation.
DSCs perform many functions formerly performed by photoprocessors for film:
Image sharpening.
Color balance.

24. File management EXIF standard gives format for digital pictures:
Format of data in a file.
Directory structure.
EXIF file includes:
Image (JPEG, etc.)
Thumbnail.
Metadata (camera type, date/time, etc.)

25. Accelerators
Example: video accelerator

26. Concept
Build accelerator for block motion estimation, one step in video compression.
Perform two-dimensional correlation: f2
Frame 1 f2 f2 f2 f2 f2 f2 f2 f2 f2

27. Block motion estimation
MPEG divides frame into 16 x 16 macroblocks for motion estimation.
Search for best match within a search range.
Measure similarity with sum-of-absolute-differences (SAD):
S | M(i,j) - S(i-ox, j-oy) |

28. Best match
Best match produces motion vector for motion block:

29. Full search algorithm bestx = 0; besty = 0; bestsad = MAXSAD;
for (ox = - SEARCHSIZE; ox < SEARCHSIZE; ox++) {
for (oy = -SEARCHSIZE; oy < SEARCHSIZE; oy++) {
int result = 0;
for (i=0; i<MBSIZE; i++) {
for (j=0; j<MBSIZE; j++) {
result += iabs(mb[i][j] - search[i-ox+XCENTER][j-oy-YCENTER]);

30. Full search algorithm, cont’d.}
if (result <= bestsad) { bestsad = result; bestx = ox; besty = oy; }

31. Computational requirements
Let MBSIZE = 16, SEARCHSIZE = 8.
Search area is in each dimension.
Must perform:
nops = (16 x 16) x (17 x 17) = ops
CIF format has 352 x 288 pixels -> 22 x 18 macroblocks.

32. Accelerator requirements

33. Accelerator data types, basic classes
Motion-vector
Macroblock
Search-area
x, y : pos
pixels[] : pixelval
pixels[] : pixelval PC
Motion-estimator
memory[]
compute-mv()

34. Sequence diagram :PC :Motion-estimator compute-mv() Search area
memory[]
memory[]
macroblocks
memory[]

35. Architectural considerations
Requires large amount of memory:
macroblock has 256 pixels;
search area has 1,089 pixels.
May need external memory (especially if buffering multiple macroblocks/search areas).

36. Motion estimator organization
PE 0
search area
network
PE 1
comparator
ctrl
Address
generator
...
Motion
vector
macroblock
network
PE 15

37. Pixel schedules
M(0,0)
S(0,2)

38. System testing Testing requires a large amount of data.
Use simple patterns with obvious answers for initial tests.
Extract sample data from JPEG pictures for more realistic tests.