next up previous
Next: Parallelism in Multi-Colored Up: Available Parallelism in Previous: Available Parallelism in

Parallelism in Block-Diagonal-Bordered Matrices

To clearly identify the available parallelism in the block-diagonal-bordered Gauss-Seidel method, we define a block diagonal partition on the matrix, apply that partition to formula gif, and equate terms to identify available parallelism. We must also define a sub-partitioning of the last diagonal block to identify parallelism after multi-coloring.

First, we define a partitioning of the system of linear equations , where the permutation matrix orders the matrix into block-diagonal-bordered form.

 

Equation gif divides the matrix into a diagonal component , a strictly lower diagonal portion of the matrix , and a strictly upper diagonal portion of the matrix such that:

 

Derivation of the block-diagonal-bordered form of the D, L, and U matrices is straightforward. Equation gif requires the calculation of , which is simple to determine explicitly, because this matrix has block-diagonal-lower-bordered form. The diagonals in are of the form:

 

and the only other non-zero terms are in the last row. These values are of the form:

 

Given these partitioned matrices, it is relatively straightforward to identify available parallelism by substituting the partitioned matrices and partitioned and vectors into the definition of the Gauss-Seidel method and then performing the matrix multiplications. As a result we obtain:

 

We can identify the parallelism in the block-diagonal-bordered portion of the matrix by examining equation gif. If we assign each partition i, , to a separate processor the calculations of are independent and require no communications. Note that the vector is required for the calculations in each partition, and there is no violation of the strict precedence rules in the Gauss-Seidel because it is calculated in the previous step. After calculating in the first m partitions, the values of must be calculated using the lower border and last block. From the previous step, the values of would be available on the processors where they were calculated, so the values of can be readily calculated in parallel. Only matrix vector products, calculated in parallel, are involved in the communications phase. Furthermore, if we assign

 

then the formulation of looks similar to equation gif:

 



next up previous
Next: Parallelism in Multi-Colored Up: Available Parallelism in Previous: Available Parallelism in



David P. Koester
Sun Oct 22 17:27:14 EDT 1995