Cache memory behavior of advanced PDE solvers

Three different partial differential equation (PDE) solver kernels are analyzed in respect to cache memory performance on a simulated shared memory computer. The kernels implement state-of-the-art solution algorithms for complex application problems, and the simulations are performed for data sets of realistic size. The performance of the studied applications benefits from much longer cache lines than normally found in commercially available computer systems. The reason for this is that numerical algorithms are carefully coded and have regular memory access patterns. These programs take advantage of spatial locality and the amount of false sharing is limited. A simple sequential hardware prefetch strategy, providing cache behavior similar to a large cache line, could potentially yield large performance gains for these applications. Unfortunately, such prefetchers often lead to additional address snoops in multiprocessor caches. However, applying a bundle technique, which lumps several read address transactions together, this large increase in address snoops can be avoided. For all studied algorithms, both the address snoops and cache misses are largely reduced in the bundled prefetch protocol.