POPL '88 Proceedings of the 15th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Compiling for numa parallel machines
Compiling for numa parallel machines
Tile size selection using cache organization and data layout
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Data-centric multi-level blocking
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Dynamic management of scratch-pad memory space
Proceedings of the 38th annual Design Automation Conference
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
Reuse-Driven Tiling for Data Locality
LCPC '97 Proceedings of the 10th International Workshop on Languages and Compilers for Parallel Computing
Efficient Utilization of Scratch-Pad Memory in Embedded Processor Applications
EDTC '97 Proceedings of the 1997 European conference on Design and Test
Multiprocessor, Multithreading and Memory Optimization for On-Chip Multimedia Applications
Journal of Signal Processing Systems
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An optimizing compiler can play an important role in enhancing data locality in array-intensive applications with regular data access patterns. This paper presents a compiler-based data space oriented tiling approach (DST). In this strategy, the data space (i.e., the array index space) is logically divided into chunks (called data tiles) and each data tile is processed in turn. In processing a data tile, our approach traverses the entire iteration space of all nests in the code and executes all iterations (potentially coming from different nests) that access the data tile being processed. In doing so, it also takes data dependences into account. Since a data space is common across all nests that access it, DST can potentially achieve better results than traditional tiling by exploiting inter-nest data locality. This paper also shows how data space oriented tiling can be used for improving the performance of software-managed scratch pad memories.