{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

David patterson etal parallel computing lab berkeley

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: with a k x k tile of B (which can fit in the cache) and thus reuses the B tile k times, better cache use "   Loops become nested loops "   outer loop visits tile origins "   inner loops visit the tile points "   We can parameterize our program with k and experiment Tiled matrix multiply Do the whole block A11 x B11 multiply Tiled matrix multiply The do block A11 x B12 multiply How many times are A and B elements used now? etc. ..... Knapsack Knapsack Problem: Bottom- Up Dynamic Programming "   Knapsack. Fill an n- by- W array. Input: n, W, w1,…,wN, v1,…,vN for w = 0 to W M[0, w] = 0 for i = 1 to n for w = 0 to W if wi > w : M[i, w] = M[i-1, w] else : M[i, w] = max (M[i-1, w], vi + M[i-1, w-wi ]) return M[n, W] Knapsack data dependence M[i, w] depends on M[i-1,w] and M[i-1,w-wi] How can we parallelize knapsack? there are no in row dependences Knapsack parallelization M[i, w...
View Full Document

{[ snackBarMessage ]}