A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Access normalization: loop restructuring for NUMA computers
ACM Transactions on Computer Systems (TOCS)
Unifying data and control transformations for distributed shared-memory machines
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Improving data locality with loop transformations
ACM Transactions on Programming Languages and Systems (TOPLAS)
Non-singular data transformations: definition, validity and applications
ICS '97 Proceedings of the 11th international conference on Supercomputing
Constraint-based array dependence analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
Improving Cache Locality by a Combination of Loop and Data Transformations
IEEE Transactions on Computers - Special issue on cache memory and related problems
A compiler technique for improving whole-program locality
POPL '01 Proceedings of the 28th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Optimizing compilers for modern architectures: a dependence-based approach
Optimizing compilers for modern architectures: a dependence-based approach
Data Relation Vectors: A New Abstraction for Data Optimizations
IEEE Transactions on Computers - Special issue on the parallel architecture and compilation techniques conference
Wireless Communications Systems: Advanced Techniques for Signal Reception
Wireless Communications Systems: Advanced Techniques for Signal Reception
Facilitating the search for compositions of program transformations
Proceedings of the 19th annual international conference on Supercomputing
An overview of the open research compiler
LCPC'04 Proceedings of the 17th international conference on Languages and Compilers for High Performance Computing
Hi-index | 0.00 |
There is a strong need now for compilers of embedded systems to find effective ways of optimizing series of loop-nests, wherein majority of the memory references occur in the form of multi-dimensional arrays, indexed primarilywith linear functions of iterators and parameterized constants. The reason for this are the new wireless standards, e.g. 802.11n, WiMAX, Bluetooth, HIPERMAN, 3GPP-LTE and WiBro, where the codes are predominantly of the type described above. These standards provide high bitrate and mobility but are also extremely power and performance hungry. For even wider commercial applicability of these standards it is important to optimize their power consumption. We propose a novel solution to multiple loop-nest optimization problem using the concept of constraints. Experiments show that our technique leads to 40.8% reduction in external memory accesses over state-of-the-art.