Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Improved Algorithms for Mapping Pipelined and Parallel Computations
IEEE Transactions on Computers
A tool for partitioning and pipelined scheduling of hardware-software systems
Proceedings of the 11th international symposium on System synthesis
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Pipelined Data Parallel Algorithms-I: Concept and Modeling
IEEE Transactions on Parallel and Distributed Systems
Stream Processors: Progammability and Efficiency
Queue - DSPs
The future of multiprocessor systems-on-chips
Proceedings of the 41st annual Design Automation Conference
Linkage Problem, Distribution Estimation, and Bayesian Networks
Evolutionary Computation
SODA: A Low-power Architecture For Software Radio
Proceedings of the 33rd annual international symposium on Computer Architecture
Sporadic model building for efficiency enhancement of hierarchical BOA
Proceedings of the 8th annual conference on Genetic and evolutionary computation
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
ILP and heuristic techniques for system-level design on network processor architectures
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Design methodology for pipelined heterogeneous multiprocessor system
Proceedings of the 44th annual Design Automation Conference
Mapping pipeline skeletons onto heterogeneous platforms
Journal of Parallel and Distributed Computing
Application partitioning on programmable platforms using the ant colony optimization
Journal of Embedded Computing - Embeded Processors and Systems: Architectural Issues and Solutions for Emerging Applications
Orchestrating the execution of stream programs on multicore platforms
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Synthesis of heterogeneous pipelined multiprocessor systems using ILP: jpeg case study
CODES+ISSS '08 Proceedings of the 6th IEEE/ACM/IFIP international conference on Hardware/Software codesign and system synthesis
Prototyping pipelined applications on a heterogeneous FPGA multiprocessor virtual platform
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Mapping task graphs onto Network Processors using genetic algorithm
AICCSA '08 Proceedings of the 2008 IEEE/ACS International Conference on Computer Systems and Applications
Pipelined data parallel task mapping/scheduling technique for MPSoC
Proceedings of the Conference on Design, Automation and Test in Europe
Macro pipelining based scheduling on high performance heterogeneousmultiprocessor systems
IEEE Transactions on Signal Processing
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In this paper we propose a flow based on the Bayesian Optimization Algorithm (BOA) for mapping pipelined applications on a heterogeneous multiprocessor platform on Field Programmable Gate Array (FPGA) with customizable processors. BOA is a Probabilistic Model Building Genetic Algorithm (PMBGA) that, substituting the classical mutation and crossover operators with the construction and the sampling of a Bayesian network, is able to identify correlated sub-structures within the problem to be maintained while generating new solutions. The paper introduces the model adopted for pipelined applications and then shows why BOA fits the problem better than other search algorithms, like Genetic Algorithm (GA), Simulated Annealing (SA) and Tabu Search (TS). We also show that our algorithm is able to cope with data parallel pipelined algorithms. We finally validate our flow on realistic applications like JPEG and ADPCM coding by executing the resulting mapping on our platform.