Integrating software caches with scratch pad memory

Abstract

Software cache refers to cache functionality emulated in software on a compiler-controlled Scratch Pad Memory (SPM). Such structures are useful when standard SPM allocation strategies cannot be used due to hard-to-analyze memory reference patterns in the source code. SPM data allocation strategies generally rely on compile-time inference of spatial and temporal reuse, with the general flow being the copying of a block/tile of array data into the SPM, followed by its processing, and finally, copying back. However, when array index functions are complicated due to conditionals, complex expressions, and dependence on run-time data, the SPM compiler has to rely on expensive DMA for individual words, leading to poor performance. Software caches (SWC) can play a crucial role in improving performance under such circumstances -- their access times are longer than those for direct SPM access, but they retain the advantages (present in hardware caches) of exploiting spatial and temporal locality discovered at run-time. We present the first automated compiler data allocation strategy that considers the presence of a software cache in SPM space, and makes decisions on which arrays should be accessed through it, at which times. Arrays could be accessed differently in different parts of a program, and our algorithm analyzes such uses and considers the possibility of selectively accessing an array through the SWC only when it is efficient, based on a cost model of the overheads involved in SPM/SWC transitions. We implemented our technique in an LLVM based framework and experimented with several applications on a Cell based machine. Our technique results in up to 82% overall performance improvement over a conventional SPM mapping algorithm and up to 27% over a typical SWC-enhanced implementation.