Can anyone help me optimize the if statements in For loops to make the code faster?

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Nadatimuj
Nadatimuj 2022-5-9
评论： Nadatimuj 2022-5-15
function [triu_adjacency,J_indices] = get_triu_adjacency(J_org, max_num_neighbors)
% J_org =[ 0 -1 -1 1 2
% -1 0 -1 1 2
% -1 -1 0 1 2
% 1 1 1 0 -2
% 2 2 2 -2 0];
%
% J_org = [ 0, +2, +0, +1, +0, -1, -1
% +2, 0, +0, -1, -1, +3, +0
% +0, +0, 0, -2, +0, +1, +1
% +1, -1, -2, 0, +2, +0, +0
% +0, -1, +0, +2, 0, +0, +1
% -1, +3, +1, +0, +0, 0, +0
% -1, +0, +1, +0, +1, +0, 0];
J_org = full(J_org);
J = triu(J_org);
num_bits = length(J_org);
%max_neighbors = max(degree(graph(J_org)));
% max_neighbors =7
counter = 1;
zero_counter =[];
triu_adjacency = zeros(num_bits, max_num_neighbors);
J_indices = zeros(size(J));
for i= 1:num_bits
n_neighbors = 1;
col_list = J(1:i,i);
for j = 1:length(col_list)
if col_list(j)
triu_adjacency(i,n_neighbors) = J_indices(j,i);
n_neighbors = n_neighbors + 1;
end
end
row_list = J(i,i+1:end);
for j = 1:length(row_list)
if row_list(j)
triu_adjacency(i,n_neighbors) = counter;
J_indices(i, j + i) = counter;
counter = counter +1;
n_neighbors = n_neighbors + 1;
end
end
for k= n_neighbors:max_num_neighbors
if isempty(zero_counter)
triu_adjacency(i, k) = counter;
zero_counter = counter;
counter = counter +1;
else
triu_adjacency(i, k) = zero_counter;
zero_counter = [];
end
end
end
end
  2 个评论
Nadatimuj
Nadatimuj 2022-5-9
编辑：Nadatimuj 2022-5-9
Thank you! A little bit difficult to explain, but I will try.
I have a symmetric matrix (undirected graph). Let's say it's a 7x7 matrix. Let's say maximum degree of the graph is 4. I now want to generate a 7x4 matrix for hardware implementation.
The rules are:
  1. Start from the J_org matrix.
  2. Label the non-zero values one by one. For each row, do it upto max degree. If number of non-zero values in a row is less than max degrees, then spend a new label for that empty space.
  3. Since it is originally a symmetric matrix, (i,j) value will be same as (j,i) values. So you will use the same label twice representaing the same value. This is true for the empty value label as well, use them twice.
  4. J_indices report the unique labels on the upper triangle of J_org. Except empty labels.
Example Input:
J_org =
[0 2 0 1 0 -1 -1
2 0 0 -1 -1 3 0
0 0 0 -2 0 1 1
1 -1 -2 0 2 0 0
0 -1 0 2 0 0 1
-1 3 1 0 0 0 0
-1 0 1 0 1 0 0]
triu_adjacency =
[ 1 2 3 4
1 5 6 7
8 9 10 11
2 5 8 12
6 12 13 11
3 7 9 14
4 10 13 14]
J_indices =
[0 1 0 2 0 3 4
0 0 0 5 6 7 0
0 0 0 8 0 9 10
0 0 0 0 12 0 0
0 0 0 0 0 0 13
0 0 0 0 0 0 0
0 0 0 0 0 0 0]

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采纳的回答

Jan
Jan 2022-5-9
The loops look fine. I'd omit the J=triu(J_org), because you use the upper triangle only inside the code
Vectorizing the inner loops increases the processing time by a factor of 2! See:
function [Adj,Index] = get_triu_adjacency(JS, nNeighbors)
% This is SLOWER then the original nested loops!!!
J = full(JS) ~= 0;
nBits = length(J);
Adj = zeros(nBits, nNeighbors);
Index = zeros(size(J));
c = 1;
z = nan;
for i = 1:nBits
col = J(1:i, i);
nc = sum(col);
Adj(i, 1:nc) = Index(col, i);
row = J(i, i+1:nBits);
nr = sum(row);
Adj(i, nc+1:nc+nr) = c:c+nr-1;
Index(i, find(row) + i) = c:c+nr-1;
c = c + nr - 1;
n = nc + nr - 1;
for k = n:nNeighbors
if isnan(z)
Adj(i, k) = c;
z = c;
c = c + 1;
else
Adj(i, k) = z;
z = nan;
end
end
end
end
I've simplified the names of the variables to reduce the clutter. Compare "n_neighbors" with a simple "n".
Setting z to NaN instead of the empty matrix might save some milliseconds. But the loop version seems to be efficient.
  3 个评论
显示 1更早的评论
Jan
Jan 2022-5-14
Measuring the timings reduces the pörocessing speed in general, not only for this code. To determine the need spent in each line, Matlab must record the timings after each command. Of course this is expensive.
In addition Matlab's profiler disables the JIT acceleration (at least partially): The JIT can reorder commands inside loops to improve the speed. But then Matlab cannot determine the time spent in a specific line anymore. This means, that the profiler has a strong influence on the processing speed - what a pity.

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