@conference {18091,
	title = {DRuiD: Designing Reconfigurable Architectures with Decision-making Support},
	booktitle = {19th Asia and South Pacific Design Automation Conference (ASP-DAC)},
	year = {2014},
	month = {01/2014},
	address = {Singapore},
	url = {http://home.deib.polimi.it/gpalermo/papers/ASPDAC14DRUID.pdf},
	author = {Mariani, Giovanni and Meeuws, Roel and Palermo, Gianluca and Sima, Vlad-Mihai and Silvano, Cristina and Bertels, Koen}
}
@article {18093,
	title = {Design-space Exploration and Runtime Resource Management for Multicores},
	journal = {ACM Transactions on Embedded Computing Systems (TECS) - Special issue on application-specific processors},
	volume = {13},
	issue = {2},
	year = {2013},
	month = {09/2013},
	pages = {20:1{\textendash}20:27},
	abstract = {Application-specific multicore architectures are usually designed by using a configurable platform in which a set of parameters can be tuned to find the best trade-off in terms of the selected figures of merit (such as energy, delay, and area). This multi-objective optimization phase is called Design-Space Exploration (DSE). Among the design-time (hardware) configurable parameters we can find the memory subsystem configuration (such as cache size and associativity) and other architectural parameters such as the instruction-level parallelism of the system processors. Among the runtime (software) configurable parameters we can find the degree of task-level parallelism associated with each application running on the platform.

The contribution of this article is twofold; first, we introduce an evolutionary (NSGA-II-based) methodology for identifying a hardware configuration which is robust with respect to applications and corresponding datasets. Second, we introduce a novel runtime heuristic that exploits design-time identified operating points to provide guaranteed throughput to each application. Experimental results show that the design-time/runtime combined approach improves the runtime performance of the system with respect to existing reference techniques, while meeting the overall power budget.},
	keywords = {application-specific platforms, design-space exploration, genetic algorithms, Multicore architectures, operating systems, resource reservation, runtime resource management, throughput maximization},
	issn = {1539-9087},
	doi = {10.1145/2514641.2514647},
	author = {Mariani, Giovanni and Palermo, Gianluca and Zaccaria, Vittorio and Silvano, Cristina}
}
@inbook {18092,
	title = {Design Space Exploration for Run-Time Management of a Reconfigurable System for Video Streaming},
	booktitle = {Multi-objective design space exploration of multiprocessor SoC architectures: the MULTICUBE approach},
	year = {2011},
	pages = {189-204},
	publisher = {Springer},
	organization = {Springer},
	edition = {1},
	isbn = {978-1-4419-8836-2},
	author = {Mariani, Giovanni and Avasare, Prabhat and Ykman-Couvreur, Chantal and Vanmeerbeeck, Geert and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio},
	editor = {Silvano, Cristina and Fornaciari, William and Villar, Eugenio}
}
@inbook {138.MaAvYkVaPaSiZa.2011,
	title = {Design Space Exploration of a Reconfigurable System for Supporting Video Streaming Run-time Management},
	booktitle = {Multi-objective design space exploration of multiprocessor SoC architectures: the MULTICUBE approach},
	year = {2011},
	publisher = {Springer},
	organization = {Springer},
	address = {New York, USA},
	abstract = {This paper reports a case study of Design Space Exploration for supporting Run-time Resource Management (RRM). In particular the management of system resources for an MPSoC dedicated to multiple MPEG4 encoding is addressed in the context of an Automotive Cognitive Safety System (ACSS). The runtime management problem is defined as the minimization of the platform power consumption under resource and Quality of Service (QoS) constraints. The paper provides an insight of both, design-time and run-time aspects of the problem. During the prelimiary design-time Design Space Exploration (DSE) phase, the best configurations of run-time tunable parameters are statically identified for providing the best trade-offs in terms of run-time costs and application QoS. To speed up the optimization process without reducing the quality of final results, a multi-simulator framework is used for modeling platform performance. At run-time, the RRM exploits the design-time DSE results for deciding an operating configuration to be loaded for each MPEG4 encoder. This operation is carried out dynamically, by following the QoS requirements of the specific use-case.},
	author = {Mariani, Giovanni and Avasare, Prabhat and Ykman-Couvreur, Chantal and Vanmeerbeeck, Geert and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio}
}
@inbook {140.KaTuPaSiZaMaBoDo.2011,
	title = {Design Space Exploration of Parallel Architectures},
	booktitle = {Multi-objective design space exploration of multiprocessor SoC architectures: the MULTICUBE approach},
	year = {2011},
	publisher = {Springer},
	organization = {Springer},
	address = {New York, USA},
	abstract = {This chapter will present two significant applications of the MULTICUBE design space exploration framework. The first part will present the design space exploration of a low power processor developed by STMicroelectronics by using the modeFRONTIER tool to demonstrate the benefits DSE not only in terms of objective quality, but also in terms of impact on the design process within the corporate environment. The second part will describe the application of RSM models developed within MULTICUBE to a tiled, multiple-instruction, many-core architecture developed by ICT China. Overall, the results have showed that different models can present a trade-off of accuracy versus computational effort. In fact, throughout the evaluation, we observed that high accuracy models require high computational time (for both model construction time and prediction time); vice-versa low model construction and prediction time has led to low accuracy.},
	author = {Kavka, Carlos and Turco, Alessandro and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio and Mariani, Giovanni and Bocchio, Sara and Dongrui, Fan}
}
@inbook {144.AvYkVaMaPaSiZa.2011,
	title = {Design Space Exploration Supporting Run-time Resource Management},
	booktitle = {Multi-objective design space exploration of multiprocessor SoC architectures: the MULTICUBE approach},
	year = {2011},
	publisher = {Springer},
	organization = {Springer},
	address = {New York, USA},
	abstract = {Running multiple applications optimally in terms of Quality of Service (e.g., performance and power consumption) on embedded multi-core platforms is a huge challenge.Moreover, current applications exhibit unpredictable changes of the environment and workload conditions which makes the task of running them optimally even more difficult. This dynamic trend in application runs will grow even more in future applications. This paper presents an automated tool flow which tackles this challenge by a two-step approach: first at design-time, a Design Space Exploration (DSE) tool is coupled with a platform simulator(s) to get optimum operating points for the set of target applications. Secondly, at run-time, a lightweight Run-time Resource Manager (RRM) leverages the design-time DSE results for deciding an operating configuration to be loaded at run-time for each application. This decision is performed dynamically, by taking into consideration available platform resources and the QoS requirements of the specific use-case. To keep RRM execution and resource overhead at minimum, a very fast optimisation heuristic is integrated. Application of this tool-flow on a real-life multimedia use case (described in Chapter 9 of the book of this paper) will demonstrate a significant speedup in optimisation process while maintaining desired Quality of Service.},
	author = {Avasare, Prabhat and Ykman-Couvreur, Chantal and Vanmeerbeeck, Geert and Mariani, Giovanni and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio}
}
@conference {98.MaPaSiZa309,
	title = {A Design Space Exploration Methodology Supporting Run-Time Resource Management for Multi-Processors System on-Chip},
	booktitle = {Proceedings IEEE SASP{\textquoteright}09 - Symposium on Application Specific Processors},
	year = {2009},
	month = {July},
	address = {San Francisco, CA, USA},
	abstract = {Application Specific 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 either at design-time or at run-time, to provide the best trade-offs in terms of the selected system figures of merit (such as power and throughput) for a dynamic application-specific workload. Among the design-time (hardware) configurable parameters we can find the memory sub-system configuration (e.g. cache size and associativity) and other architectural parameters such as the instruction-level parallelism of the system processors. Among the run-time (software) configurable parameters we can find the overall degree of task-level parallelism associated with each application running on the chip. Typically, while the design-time exploration is performed in the early development stages for a set of static parameters, the tuning of the run-time parameters is performed dynamically by a run-time management software module after the system has been deployed. In this paper, we introduce a methodology for identifying a hardware configuration which is robust with respect to the variable workload scenario introduced by the run-time management. Moreover, the proposed methodology is aimed at providing useful information about the optimal software operating points of the applications in terms of task-level parallelism. The proposed methodology is based on the NSGA-II evolutionary heuristic algorithm assisted by an Artificial Neural Network (ANN). We then introduce a run-time management policy which is able to exploit the above information to maximize the performance of the system under power budget constraints. Experimental results show that the proposed technique is able to reduce the overall design space exploration time yet providing a near-optimal solution, in terms of hardware parameters, to enable an innovative and efficient run-time anagement policy.},
	keywords = {artificial neural network, design space exploration, meta-model assisted optimization, multi-objective optimization, multiprocessor system-on-chip (MPSoC), run-time resource management},
	doi = {http://dx.doi.org/10.1109/SASP.2009.5226331},
	author = {Mariani, Giovanni and Palermo, Gianluca and Silvano, Cristina and Zaccaria, Vittorio}
}
