How to use CUDA programming to calculate and process the correct number
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Bandwidth test - test memory bandwidth.
Especially important for PCIE capability. Different MB has different PCIE capability.
The CUDA adaptor performance is depend on the capability of PCIE. It could be the performance bottleneck.
On the following programming drills, the number of clock cycles necessary for computation and utilised memory bandwidth have to be computing.
(1) parallelization in the programs - using 256 threads
(2) improving the memory access modes
(3) testing the parallelization by using 512/1024
(4) utilizing BLOCKS in the computation
(5) utilizing shared memory
(6) improving the computation oerfdormance by using a Treesum algorithm
(7) resolving the memory band conflict issue, encountered in applying Treesum algorithm with the shared memory
-
Bandwidth test - test memory bandwidth.
Especially important for PCIE capability. Different MB has different PCIE capability.
The CUDA adaptor performance is depend on the capability of PCIE. It could be the performance bottleneck.
On the following programming drills, the number of clock cycles necessary for computation and utilised memory bandwidth have to be computing.
(1) parallelization in the programs - using 256 threads
(2) improving the memory access modes
(3) testing the parallelization by using 512/1024
(4) utilizing BLOCKS in the computation
(5) utilizing shared memory
(6) improving the computation oerfdormance by using a Treesum algorithm
(7) resolving the memory band conflict issue, encountered in applying Treesum algorithm with the shared memory
-
Bandwidth test - test memory bandwidth.
Especially important for PCIE capability. Different MB has different PCIE capability.
The CUDA adaptor performance is depend on the capability of PCIE. It could be the performance bottleneck.
On the following programming drills, the number of clock cycles necessary for computation and utilised memory bandwidth have to be computing.
(1) parallelization in the programs - using 256 threads
(2) improving the memory access modes
(3) testing the parallelization by using 512/1024
(4) utilizing BLOCKS in the computation
(5) utilizing shared memory
(6) improving the computation oerfdormance by using a Treesum algorithm
(7) resolving the memory band conflict issue, encountered in applying Treesum algorithm with the shared memory
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