The 'start' parameter defines the initial centroid locations. As the help explains, it should be k-by-p where k is the number of groups you're splitting the data into. If you use the data matrix itself, then k is the same as the number of data points! That is, your asking kmeans to group n points into n groups! The result will be that each data point is in its own group. If you have 300,000 points, you'll also run out of memory, it seems.
This is what you're trying to do:
X = rand(20,2);
g = kmeans(X,[],'start',X)
gscatter(X(:,1),X(:,2),g)
This is what you should be doing:
g = kmeans(X,[],'start',[0.25,0.75;0.25,0.25;0.75,0.25;0.75,0.75])
gscatter(X(:,1),X(:,2),g)
Note that the data (X) is 20-by-2. The starting matrix is 4-by-2, so kmeans makes 4 groups out of the 20 points.
