Optimal weighted loop fusion for parallel programs
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
Maximizing parallelism and minimizing synchronization with affine partitions
Parallel Computing - Special issues on languages and compilers for parallel computers
Proceedings of the 14th international conference on Supercomputing
Maximizing Loop Parallelism and Improving Data Locality via Loop Fusion and Distribution
Proceedings of the 6th International Workshop on Languages and Compilers for Parallel Computing
Semi-automatic composition of loop transformations for deep parallelism and memory hierarchies
International Journal of Parallel Programming
Compilers: Principles, Techniques, and Tools (2nd Edition)
Compilers: Principles, Techniques, and Tools (2nd Edition)
Profitable loop fusion and tiling using model-driven empirical search
Proceedings of the 20th annual international conference on Supercomputing
Parameterized tiled loops for free
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
A practical automatic polyhedral parallelizer and locality optimizer
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Outer-loop vectorization: revisited for short SIMD architectures
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
Compact multi-dimensional kernel extraction for register tiling
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
CC'08/ETAPS'08 Proceedings of the Joint European Conferences on Theory and Practice of Software 17th international conference on Compiler construction
Combined Iterative and Model-driven Optimization in an Automatic Parallelization Framework
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
The polyhedral model is more widely applicable than you think
CC'10/ETAPS'10 Proceedings of the 19th joint European conference on Theory and Practice of Software, international conference on Compiler Construction
Polyhedral code generation in the real world
CC'06 Proceedings of the 15th international conference on Compiler Construction
Loop transformations: convexity, pruning and optimization
Proceedings of the 38th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Optimizing memory hierarchy allocation with loop transformations for high-level synthesis
Proceedings of the 49th Annual Design Automation Conference
Tiling stencil computations to maximize parallelism
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Code generation for parallel execution of a class of irregular loops on distributed memory systems
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
PolyGLoT: a polyhedral loop transformation framework for a graphical dataflow language
CC'13 Proceedings of the 22nd international conference on Compiler Construction
Revisiting loop fusion in the polyhedral framework
Proceedings of the 19th ACM SIGPLAN symposium on Principles and practice of parallel programming
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Loop fusion has been studied extensively, but in a manner isolated from other transformations. This was mainly due to the lack of a powerful intermediate representation for application of compositions of high-level transformations. Fusion presents strong interactions with parallelism and locality. Currently, there exist no models to determine good fusion structures integrated with all components of an auto-parallelizing compiler. This is also one of the reasons why all the benefits of optimization and automatic parallelization of long sequences of loop nests spanning hundreds of lines of code have never been explored. We present a fusion model in an integrated automatic parallelization framework that simultaneously optimizes for hardware prefetch stream buffer utilization, locality, and parallelism. Characterizing the legal space of fusion structures in the polyhedral compiler framework is not difficult. However, incorporating useful optimization criteria into such a legal space to pick good fusion structures is very hard. The model we propose captures utilization of hardware prefetch streams, loss of parallelism, as well as constraints imposed by privatization and code expansion into a single convex optimization space. The model scales very well to program sections spanning hundreds of lines of code. It has been implemented into the polyhedral pass of the IBM XL optimizing compiler. Experimental results demonstrate its effectiveness in finding good fusion structures for codes including SPEC benchmarks and large applications. An improvement ranging from 5% to nearly a factor of 2.75x is obtained over the current production compiler optimizer on these benchmarks.