PNX1300 Philips, PNX1300 Datasheet - Page 80
PNX1300
Manufacturer Part Number
PNX1300
Description
Media Processors
Manufacturer
Philips
Datasheet
1.PNX1300.pdf
(548 pages)
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PNX1300/01/02/11 Data Book
Figure 4-8. Final version of the frame-reconstruction code.
Figure 4-9
cost loop. Unlike the previous example, the code is not a
self-contained function. Somewhere early in the code,
the arrays A[][] and B[][] are declared; somewhere be-
tween those declarations and the loop of interest, the ar-
rays are filled with data.
4.4.1
First, we will look at the simplest way to use a PNX1300
custom operation.
We start by noticing that the computation in the loop of
Figure 4-9
of two unsigned characters (bytes). By now, we are fa-
miliar with the fact that PNX1300 includes a number of
operations that process all four bytes in a 32-bit word si-
multaneously. Since the match-cost calculation is funda-
mental to the MPEG algorithm, it is not surprising to find
4-8
Figure 4-9. Match-cost loop for MPEG motion estimation.
Figure 4-10. Unrolled, but not parallel, version of the loop from
A Simple Transformation
void reconstruct (unsigned char *back,
{
}
shows the original source code for the match-
involves the absolute value of the difference
int i;
int *i_back
int *i_forward = (int *) forward;
int *i_idct
int *i_dest
for (i = 0; i < 16; i += 1)
unsigned char A[16][16];
unsigned char B[16][16];
for (row = 0; row < 16; row += 1)
{
i_dest[i] = DSPUQUADADDUI(QUADAVG(i_back[i], i_forward[i]), i_idct[i]);
unsigned char A[16][16];
unsigned char B[16][16];
for (row = 0; row < 16; row += 1)
{
}
for (col = 0; col < 16; col += 4)
{
PRELIMINARY SPECIFICATION
for (col = 0; col < 16; col += 1)
.
.
.
cost += abs(A[row][col+0] – B[row][col+0]);
cost += abs(A[row][col+1] – B[row][col+1]);
cost += abs(A[row][col+2] – B[row][col+2]);
cost += abs(A[row][col+3] – B[row][col+3]);
.
.
.
cost += abs(A[row][col] – B[row][col]);
unsigned char *forward,
unsigned char *destination)
= (int *) back;
= (int *) idct;
= (int *) destination;
char *idct,
a custom operation—ume8uu—that implements this op-
eration exactly.
To understand how ume8uu can be used in this case, we
need to transform the code as in the previous example.
Though the steps are presented here in detail, a pro-
grammer with a even a little experience can often per-
form these transformations by visual inspection.
To use a custom operation that processes 4 pixel values
simultaneously, we first need to create 4 parallel pixel
computations.
unrolled by a factor of 4. Unfortunately, the code in the
unrolled loop is not parallel because each line depends
on the one above it.
version of the code from
each computation its own cost variable and then sum-
ming the costs all at once, each cost computation is com-
pletely independent.
Figure
Figure 4-10
4-9.
Figure 4-11
Figure
Philips Semiconductors
shows the loop of
4-10. By simply giving
shows a more parallel
Figure 4-9
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