Consider the bellow code. This code is supposed to be processing data at a fixed rate, in one second batches, It is part of an overal system and can't take up too much time.
When running over 100 lots of 1 seconds worth of data the program takes 35 seconds (or 35%), executing this function in a loop. The test loop is timed specifically with Ada.RealTime. The data is pregenerated so the majority of the execution time is definatetly in this loop.
How do I improce the code to get the processing time down to a minimum?
The code will be running on an Intel Pentium-M which is a P3 with SSE2.
package FF is new Ada.Numerics.Generic_Elementary_Functions(Float);
N : constant Integer := 820;
type A is array(1 .. N) of Float;
type A3 is array(1 .. 3) of A;
procedure F(state : in out A3;
result : out A3;
l : in A;
r : in A) is
s : Float;
t : Float;
begin
for i in 1 .. N loop
t := l(i) + r(i);
t := t / 2.0;
state(1)(i) := t;
state(2)(i) := t * 0.25 + state(2)(i) * 0.75;
state(3)(i) := t * 1.0 /64.0 + state(2)(i) * 63.0 /64.0;
for r in 1 .. 3 loop
s := state(r)(i);
t := FF."**"(s, 6.0) + 14.0;
if t > MAX then
t := MAX;
elsif t < MIN then
t := MIN;
end if;
result(r)(i) := FF.Log(t, 2.0);
end loop;
end loop;
end;
psuedocode for testing
create two arrays of 80 random A3 arrays, called ls and rs;
init the state and result A3 array
record the realtime time now, called last
for i in 1 .. 100 loop
for j in 1 .. 80 loop
F(state, result, ls(j), rs(j));
end loop;
end loop;
record the realtime time now, called curr
output the duration between curr and last
