In certain types of programs, re-ordering their execution can speed them up by optimizing memory accesses and parallelism. However, these re-orderings are constrained by the fact that updates depend on the results of earlier ...
The growth in speed seen in modern processors over the past couple decades has created a need for programs that carefully manage the data fed to CPUs. Often, it is the case the processors are so fast, the memory used to ...
Iterative stencil computations are important in scientific computing and in the mobile domain among others. Tiling is an important method to improve computational efficiency in GPUs, enhancing data reuse and cache memory ...
Parallel and clustered implementations of scientific computing algorithms, while fast, can be very difficult for a human to parse. This is because the industry standard method of writing parallel code is to use complicated ...