@inbook {17734,
	title = {The MULTICUBE Design Flow},
	booktitle = {Multi-objective Design Space Exploration of Multiprocessor SoC Architectures},
	year = {2011},
	pages = {3-17},
	publisher = {Springer New York},
	organization = {Springer New York},
	isbn = {978-1-4419-8836-2},
	doi = {10.1007/978-1-4419-8837-9_1},
	url = {http://dx.doi.org/10.1007/978-1-4419-8837-9_1},
	author = {Silvano, Cristina and Fornaciari, William and Palermo, Gianluca and Zaccaria, Vittorio and Castro, Fabrizio and Martinez, Marcos and Bocchio, Sara and Zafalon, Roberto and Avasare, Prabhat and Vanmeerbeeck, Geert and Ykman-Couvreur, Chantal and Wouters, Maryse and Kavka, Carlos and Onesti, Luka and Turco, Alessandro and Bondi, Umberto and Mariani, Giovanni and Posadas, Hector and Villar, Eugenio and Wu, Chris and Dongrui, Fan and Hao, Zhang},
	editor = {Silvano, Cristina and Fornaciari, William and Villar, Eugenio}
}
@inbook {139.Sietal2.2011,
	title = {MULTICUBE: Multi-Objective Design Space Exploration of Multi-Core Architectures},
	booktitle = {VLSI 2010 Annual Symposium},
	volume = {105},
	year = {2011},
	pages = {47-63},
	publisher = {Springer},
	organization = {Springer},
	address = {Netherlands},
	abstract = {Given the increasing complexity of Chip Multi-Processors (CMPs), a wide range of architecture parameters must be explored at design time to find the best trade-off in terms of multiple competing objectives (such as energy, delay, bandwidth, area, etc.) The design space of the target architectures is huge because it should consider all possible combinations of each hardware parameter (e.g., number of processors, processor issue width, L1 and L2 cache sizes, etc.). In this complex scenario, intuition and past experience of design architects is no more a sufficient condition to converge to an optimal design of the system. Indeed, Automatic Design Space Exploration (DSE) is needed to systematically support the analysis and quantitative comparison of a large amount of design alternatives in terms of multiple competing objectives (by means of Pareto analysis). The main goal of the MULTICUBE project consists of the definition of an automatic Design Space Exploration framework to support the design of next generation many-core architectures.},
	isbn = {978-94-007-1487-8},
	url = {http://dx.doi.org/10.1007/978-94-007-1488-5_4},
	author = {Silvano, Cristina and Fornaciari, William and Palermo, Gianluca and Zaccaria, Vittorio and Castro, Fabrizio and Martinez, Marcos and Bocchio, Sara and Zafalon, Roberto and Avasare, Prabhat and Vanmeerbeeck, Geert and Ykman-Couvreur, Chantal and Wouters, Maryse and Kavka, Carlos and Onesti, Luka and Turco, Alessandro and Bondi, Umberto and Mariani, Giovanni and Posadas, Hector and Villar, Eugenio and Wu, Chris and Dongrui, Fan and Hao, Zhang and Shibin, Tang}
}
@conference {136.FiPaSi10,
	title = {A Monitoring System for NoCs},
	booktitle = {Proceedings of the Third International Workshop on Network on Chip Architectures (NoCArc{\textquoteright}2010)},
	year = {2010},
	month = {December},
	address = {Atlanta, Georgia, USA},
	abstract = {In this paper, we propose and discuss a monitoring architecture for Networks-on-Chip (NoCs) that provides system information useful for helping designers in efficiently exploiting resources available in new complex Multiprocessor System-on-Chip (MPSoC) platforms, and in understanding their behavior. We focus on the analysis of the architectural details and design challenges of such systems, by describing power- ful tools for detecting information that can be used both at run-time for detecting dynamic changes in system behavior and at post-execution time for debugging and profiling of applications. We detail the design of the probes monitoring the events and discuss an architecture for collection, storage, and analysis of information generated by them. We evaluate cost of the implementation of the system in terms of area and traffic overhead, and we present results obtained when monitoring a use-case multimedia application.},
	keywords = {hardware counters, network-on-chip (NoC), performance monitoring, system-on-chip (SoC)},
	author = {Fiorin, Leandro and Palermo, Gianluca and Silvano, Cristina}
}
@conference {115.ZaPaCaSiMa10,
	title = {Multicube Explorer: An Open Source Framework for Design Space Exploration of Chip Multi-Processors},
	booktitle = {2PARMA: Proceedings of the Workshop on Parallel Programming and Run-time Management Techniques for Many-core Architectures},
	year = {2010},
	month = {February},
	address = {Hannover, Germany},
	abstract = {Given the increasing complexity of Chip Multi-Processors (CMPs), a wide range of architecture parameters must be explored at design time to find the best trade-off in terms of multiple competing objectives (such as energy, delay, bandwidth, area, etc.) The design space of the target architecture is huge because of it should consider all possible combinations of each parameter (number of processors, processor issue width, L1 and L2 cache sizes, etc.). In this complex scenario, the multi-objective exploration of the huge design space of next generation CMPs cannot be anymore based on intuition and past experience of the design architects. An Automatic Design Space Exploration methodology is needed to support systematically the exploration and the quantitative comparison of the design alternatives in terms of multiple competing objectives (Pareto analysis). An overall design space exploration framework is needed to combine all optimizations into a global search space with a common interface to the simulation and evaluation tools. Our work1 focuses on the definition of an automatic multi-objective Design Space Exploration (DSE) framework for tuning Chip Multi-Processor architectures by evaluating a set of metrics (such as energy and delay) for the next generation embedded computing platforms. Multicube Explorer is an interactive open-source framework to enable the designer to automatically explore a design space of configurations for a parameterized architecture for which an executable model (use case simulator) exists. Multicube Explorer is an advanced multi-objective optimization framework which is entirely command-line/script driven and can be re-targeted to any configurable platform by writing a suitable XML design space definition file and providing a configurable simulator},
	author = {Zaccaria, Vittorio and Palermo, Gianluca and Castro, Fabrizio and Silvano, Cristina and Mariani, Giovanni}
}
@conference {129.Sietal.ISVLSI11,
	title = {Multicube: Multi-objective design space exploration of multi-core architectures},
	booktitle = {ISVLSI 2010: IEEE Annual Symposium on VLSI},
	year = {2010},
	month = {July},
	pages = {488{\textendash}493},
	address = {Lixouri, Kefalonia - Greece},
	abstract = {Technology trends enable the integration of many processor cores in a System-on-Chip (SoC). In these complex architectures, several architectural parameters can be tuned to find the best trade-off in terms of multiple metrics such as energy and delay. The main goal of the MULTICUBE project consists of the definition of an automatic Design Space Exploration framework to support the design of next generation many-core architectures.},
	doi = {http://dx.doi.org/10.1109/ISVLSI.2010.67},
	author = {Silvano, Cristina and Fornaciari, William and Palermo, Gianluca and Zaccaria, Vittorio and Castro, Fabrizio and Martinez, Marcos and Bocchio, Sara and Zafalon, Roberto and Avasare, Prabhat and Vanmeerbeeck, Geert and Ykman-Couvreur, Chantal and Wouters, Maryse and Kavka, Carlos and Onesti, Luka and Turco, Alessandro and Bondi, Umberto and Mariani, Giovanni and Posadas, Hector and Villar, Eugenio and Wu, Chris and Dongrui, Fan and Hao, Zhang and Shibin, Tang}
}
@conference {101.MaPaSiZa209,
	title = {Meta-model Assisted Optimization for Design Space Exploration of Multi-Processor Systems-on-Chip},
	booktitle = {Euromicro Proceedings of DSD{\textquoteright}09 - Conference on Digital System Design},
	year = {2009},
	month = {August},
	address = {Patras, Greece},
	abstract = {Multi-processor Systems-on-chip are currently designed by using platform-based synthesis techniques. In this approach, a wide range of platform parameters are tuned to find the best trade-offs in terms of the selected system figures of merit (such as energy, delay and area). This optimization phase is called Design Space Exploration (DSE) and it generally consists of a Multi-Objective Optimization (MOO) problem. The design space of a Multi-processor architecture is too large to e evaluated comprehensively. So far, several heuristic techniques have been proposed to address the MOO problem, but they are haracterized by low efficiency to identify the Pareto front. In this paper, we address the MPSoC DSE problem by using an NSGA-II modified to be assisted by an Artificial Neural Network (ANN). In particular we exploit statistical methods to compute the prediction confidence intervals for the ANN approximations. These information are adopted in the evolution control strategy in order to carefully select which individuals should be simulated. Experimental results show that the proposed techniques is able to reduce the simulations needed for the optimization without decreasing the quality of the obtained Pareto Front. Results are compared with state of the art techniques to demonstrate that optimization time due to simulation can be speed up by adopting statistical methods during evolution control.},
	keywords = {artificial neural network, meta-model assisted optimization, multi-objective optimization, multiprocessor system-on-chip (MPSoC)},
	doi = {http://dx.doi.org/10.1109/DSD.2009.154},
	author = {Mariani, Giovanni and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio}
}
@conference {95.FiPaSi09,
	title = {MPSoCs Run-Time Monitoring through Networks-on-Chip},
	booktitle = {The 2009 Conference on Design, Automation and Test In Europe (DATE{\textquoteright}09)},
	year = {2009},
	month = {April/2009},
	address = {Nice, France},
	abstract = {Networks-on-Chip (NoCs) have appeared as design strategy to overcome the limitations, in terms of scalability, efficiency, and power consumption of current buses. In this paper, we discuss the idea of using NoCs to monitor system behaviour at run-time by tracing activities at initiators and targets. Main goal of the monitoring system is to retrieve information useful for run-time optimization and resources allocation in adaptive systems. Information detected by probes embedded within NIs is sent to a central unit, in charge of collecting and elaborating the data. We detail the design of the basic blocks and analyse the overhead associated with the ASIC implementation of the monitoring system, as well as discussing implications in terms of the additional traffic generated in the NoC.},
	keywords = {monitoring, network-on-chip (NoC)},
	author = {Fiorin, Leandro and Palermo, Gianluca and Silvano, Cristina}
}
@conference {96.MaPaSiZa09.2,
	title = {Multicube Explorer - A Design Space Exploration Framework for Embedded Systems-on-Chip},
	booktitle = {Proceedings of the DATE{\textquoteright}09 workshop on Designing for Embedded Parallel Computing Platforms: Architectures, Design Tools, and Applications},
	year = {2009},
	month = {April},
	address = {Nice, France},
	abstract = {Multicube Explorer is a design space exploration tool for supporting platform-based design. It allows a fast optimization of parameterized system architecture towards a set of objective functions (e.g., energy, delay and area), by interacting with a system-level simulator. Multicube Explorer provides a set of innovative sampling and optimization techniques to help finding the best objective function trade-offs. It also provides an open XML interface for supporting new platforms/architectures.},
	keywords = {area, delay, energy, fast optimization, multicube explorer, optimization techniques, platform-based design, system-level simulator, XML},
	author = {Mariani, Giovanni and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio}
}
@conference {97.Silvanoetal09,
	title = {MULTICUBE: Multi-Objective Design Space Exploration of Multiprocessor Architectures for Embedded Multimedia Applications},
	booktitle = {Proceedings of the DATE{\textquoteright}09 workshop on Designing for Embedded Parallel Computing Platforms: Architectures, Design Tools, and Applications},
	year = {2009},
	month = {April},
	address = {Nice, France},
	author = {Silvano, Cristina and Palermo, Gianluca and Zaccaria, Vittorio and Fornaciari, William and Zafalon, Roberto and Bocchio, Sara and Martinez, Marcos and Wouters, Maryse and Vanmeerbeeck, Geert and Avasare, Prabhat and Onesti, Luka and Kavka, Carlos and Bondi, Umberto and Mariani, Giovanni and Villar, Eugenio and Posadas, Hector and Wu, Chris and Dongrui, Fan and Hao, Zhang}
}
@conference {99.MaPaSiZa09,
	title = {Multiprocessor System-on-Chip Design Space Exploration based on Multi-level Modeling Techniques},
	booktitle = {Proceedings of IEEE IC-SAMOS{\textquoteright}09 - International Conference on Embedded Computer Systems: Architectures, MOdeling, and Simulation},
	year = {2009},
	month = {July},
	address = {Samos, Greece},
	abstract = {Multi-processor Systems-on-chip are currently designed by using platform-based synthesis techniques. In this approach, a wide range of platform parameters are tuned to find the best trade-offs in terms of the selected system figures of erit (such as energy, delay and area). This optimization phase is called Design Space Exploration (DSE) and it generally consists of a Multi-Objective Optimization (MOO) problem. The design space of a Multi-processor architecture is too large to be evaluated comprehensively. So far, several heuristic techniques have been proposed to address the MOO problem, but they are haracterized by low efficiency to identify the Pareto set. In this paper we propose a methodology for heuristic platform based design based on evolutionary algorithms and multi-level simulation techniques. In particular, we extend the NSGA-II with an approximate neural network meta-model for multi-processor architectures in order to replace expensive platform simulations with fast meta-model evaluation. The model accuracy and efficiency is improved by exploiting high-level platform simulation techniques. High-level simulation allows us to reduce the overall complexity of the neural network and improving its prediction power. Experimental results show that the proposed techniques is able to reduce the number of simulations needed for the optimization without decreasing the quality of the obtained Pareto set. Results are compared with state of the art echniques to demonstrate that optimization time due to simulation can be sped up by adopting multi-level simulation techniques.},
	keywords = {artificial neural network, design space exploration, genetic algorithm, multi level modelling, multiprocessor system-on-chip (MPSoC), platform-based design},
	doi = {http://dx.doi.org/10.1109/ICSAMOS.2009.5289222},
	author = {Mariani, Giovanni and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio}
}
@conference {57.PaMaSiLoCo07,
	title = {Mapping and Topology Customization Approaches for Application-Specific STNoC Designs},
	booktitle = {IEEE Proceedings of ASAP{\textquoteright}07 - 18th International Conference on Application-specific Systems, Architectures and Processors},
	year = {2007},
	month = {July},
	address = {Montr{\'e}al, Qu{\'e}bec, Canada},
	abstract = {Application-specific network-oriented communication architectures have recently become an effective solution to support high bandwidth Systems on-Chip. The Network on-Chip architectures considered so far range from regular to fully customized topologies for application specific designs requiring high-level bandwidth. To this end, a networkcentric design flow is necessary to support the design space exploration of complex SoCs with tight design constraints. This paper introduces four different approaches based on the orthogonalization of core mapping and topology customization applied to STNoC, the Network on-Chip developed by STMicroelecronics. The four methods are derived from the combination of the initial mappings to two standard topologies (ring and spidergon) with two types of topology customization based on the insertion of cross-links to reduce the network distance of standard topologies},
	keywords = {application specific design, mapping, network-on-chip (NoC), STNoC, topology customization},
	doi = {http://dx.doi.org/10.1109/ASAP.2007.4429959},
	author = {Palermo, Gianluca and Mariani, Giovanni and Silvano, Cristina and Locatelli, Riccardo and Coppola, Marcello}
}
