Multi-level Tiling Interactions
Jeanne Ferrante, Nicholas Mitchell, Karin Hogstedt, Larry
Carter
University of California, San Diego
Optimizations, including tiling, often target a single level of memory
or parallelism, such as cache. These optimizations usually operate on
a level-by-level basis, guided by a cost function parameterized by
features of that single level. The benefits of optimizations guided
by these one-level cost functions decreases as architectures tend
towards a hierarchy of memory and of parallelism. We have identified
three common architectural scenarios where a single tiling choice
could be improved by using information from multiple levels in
concert. For each scenario, we derive multi-level cost functions
which guide the optimal choice of tile size and shape, and quantify
the improvement gained. We give both analysis and simulation results
to support our points.
Further info and related paper(s):