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Suppose I have a table A stored in the PS table. I partition the table A into n x m blocks, where A(i,j) denotes the (i,j)-th block by rows and columns.
Each time I need to update just ONE block of the table A in each thread. Suppose a thread needs to update the block A(i,j), but it needs to use ALL the elements in A to calculate the update of block A(i,j). Thus, It needs to read every line of A, which I think would slow down the program. Do you have any idea to avoid reading all the data in A?
Different with Matrix Factorization:
To update the i-th row of L and j-th column of R for each thread, MF doesn't need to use all the data in L and R table.
-Junjie
The text was updated successfully, but these errors were encountered:
Let me make it more clear. I mean that all the data in table A should be used in each iteration. For example,
void runnable(int localThreadId){
// I need to use all the value in table A to calculate the updated value of A
wtw = v' * A * v
//**here, I need to use all the data in A by get() lines by lines, which is time-consuming.
// different with MF, MF just needs to get L(i) and R(j) instead of the whole matrix
Suppose I have a table A stored in the PS table. I partition the table A into n x m blocks, where A(i,j) denotes the (i,j)-th block by rows and columns.
Each time I need to update just ONE block of the table A in each thread. Suppose a thread needs to update the block A(i,j), but it needs to use ALL the elements in A to calculate the update of block A(i,j). Thus, It needs to read every line of A, which I think would slow down the program. Do you have any idea to avoid reading all the data in A?
Different with Matrix Factorization:
To update the i-th row of L and j-th column of R for each thread, MF doesn't need to use all the data in L and R table.
-Junjie
The text was updated successfully, but these errors were encountered: