Compile-Time Scheduling and Assignment of Data-Flow Program Graphs with Data-Dependent Iteration
IEEE Transactions on Computers
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A stream compiler for communication-exposed architectures
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
StreamIt: A Language for Streaming Applications
CC '02 Proceedings of the 11th International Conference on Compiler Construction
Cache aware optimization of stream programs
LCTES '05 Proceedings of the 2005 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
Queue - Multiprocessors
Data and Computation Transformations for Brook Streaming Applications on Multiprocessors
Proceedings of the International Symposium on Code Generation and Optimization
An Application of Extreme Value Theory for Measuring Financial Risk
Computational Economics
Exploiting coarse-grained task, data, and pipeline parallelism in stream programs
Proceedings of the 12th international conference on Architectural support for programming languages and operating systems
Orchestrating the execution of stream programs on multicore platforms
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Mapping stream programs onto heterogeneous multiprocessor systems
CASES '09 Proceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems
A streaming machine description and programming model
SAMOS'07 Proceedings of the 7th international conference on Embedded computer systems: architectures, modeling, and simulation
Orchestration by approximation: mapping stream programs onto multicore architectures
Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems
Optimal task assignment in multithreaded processors: a statistical approach
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
Measurement-Based Probabilistic Timing Analysis for Multi-path Programs
ECRTS '12 Proceedings of the 2012 24th Euromicro Conference on Real-Time Systems
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One of the greatest challenges in computer architecture is how to write efficient, portable, and correct software for multi-core processors. A promising approach is to expose more parallelism to the compiler, through the use of domain-specific languages. The compiler can then perform complex transformations that the programmer would otherwise have had to do. Many important applications related to audio and video encoding, software radio and signal processing have regular behavior that can be represented using a stream programming language. When written in such a language, a portable stream program can be automatically mapped by the stream compiler onto multicore hardware. One of the most difficult tasks of the stream compiler is partitioning the stream program into software threads. The choice of partition significantly affects performance, but finding the optimal partition is an NP-complete problem. This paper presents a method, based on Extreme Value theory (EVT), that statistically estimates the performance of the optimal partition. Knowing the optimal performance improves the evaluation of any partitioning algorithm, and it is the most important piece of information when deciding whether an existing algorithm should be enhanced. We use the method to evaluate a recently-published partitioning algorithm based on a heuristic. We further analyze how the statistical method is affected by the choice of sampling method, and we recommend how sampling should be done. Finally, since a heuristic-based algorithm may not always be available, the user may try to find a good partition by picking the best from a random sample. We analyze whether this approach is likely to find a good partition. To the best of our knowledge, this study is the first application of EVT to a graph partitioning problem.