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The continuous scaling of nanoelectronics is increasing the complexity of chip multiprocessors (CMPs) and exacerbating the memory wall problem. As CMPs become more complex, the memory subsystem is organized into more hierarchical structures to better exploit locality. To efficiently discover promising architectures within the rapidly growing search space, exhaustive exploration is replaced with tools that implement intelligent search strategies. Moreover, faster analytical models are preferred to costly simulations for estimating the performance and power of CMP architectures. The memory traffic generated by CMP cores has a cyclic dependency with the latency of the memory subsystem, which critically affects the overall system performance. Based on this observation, a novel scalable analytical method is proposed to estimate the performance of highly parallel CMPs (hundreds or thousands of cores) with hierarchical interconnect networks. The method can use customizable probabilistic models and solves the cyclic dependencies between traffic and latency by using a fixed-point strategy. By using the analytical model as a performance and power estimator, an efficient metaheuristic-based search is proposed for the exploration of large design spaces. The proposed techniques are shown to be very accurate and a promising strategy when compared to the results obtained by simulation., Peer Reviewed, Postprint (published version)

Tiled hierarchical architectures for Chip Multiprocessors (CMPs) represent a rapid way of building scalable and power-e fficient many-core computing systems. At the early stages of the design of a CMP, physical parameters are often ignored and postponed for later design stages. In this work, the importance of physical-aware system-level exploration is investigated, and a strategy for deriving chip floorplans is described. Additionally, wire planning of the on-chip interconnect is performed, as its topology and organization aff ect the physical layout of the system. Traditional algorithms for floorplanning and wire planning are customized to include physical constraints speci c for tiled hierarchical architectures. Over-the-cell routing is used as one of the major area savings strategy. The combination of architectural exploration and physical planning is studied with an example and the impact of the physical aspects on the selection of architectural parameters is evaluated., Postprint (author’s final draft)

This paper presents an integrated flow for architectural exploration and physical planning of large-scale hierarchical tiled CMPs. Classical floorplanning and wire planning techniques have been adapted to incorporate layout constraints that enforce regularity in the interconnect networks. Routing is performed on top of memories and components that underutilize the available metal layers for interconnectivity. The experiments demonstrate the impact of physical parameters in the selection of the most efficient architectures. Thus, the integrated flow contributes to deliver physically-viable architectures and simplify the complex design closure of large-scale CMPs., Peer Reviewed, Postprint (published version)

The microprocessor technology has experienced an enormous growth during the last decades. Rapid downscale of the CMOS technology has led to higher operating frequencies and performance densities, facing the fundamental issue of power dissipation. Chip Multiprocessors (CMPs) have become the latest paradigm to improve the power-performance efficiency of computing systems by exploiting the parallelism inherent in applications. Industrial and prototype implementations have already demonstrated the benefits achieved by CMPs with hundreds of cores.CMP architects are challenged to take many complex design decisions. Only a few of them are:- What should be the ratio between the core and cache areas on a chip?- Which core architectures to select?- How many cache levels should the memory subsystem have?- Which interconnect topologies provide efficient on-chip communication?These and many other aspects create a complex multidimensional space for architectural exploration. Design Automation tools become essential to make the architectural exploration feasible under the hard time-to-market constraints. The exploration methods have to be efficient and scalable to handle future generation on-chip architectures with hundreds or thousands of cores.Furthermore, once a CMP has been fabricated, the need for efficient deployment of the many-core processor arises. Intelligent techniques for task mapping and scheduling onto CMPs are necessary to guarantee the full usage of the benefits brought by the many-core technology. These techniques have to consider the peculiarities of the modern architectures, such as availability of enhanced power saving techniques and presence of complex memory hierarchies.This thesis has several objectives. The first objective is to elaborate the methods for efficient analytical modeling and architectural design space exploration of CMPs. The efficiency is achieved by using analytical models instead of simulation, and replacing the exhaustive exploration with a, Postprint (published version)

The complexity of large Chip Multiprocessors (CMP) makes design reuse a practical approach to reduce the manufacturing and design cost of high-performance systems. This paper proposes techniques for static task mapping onto general-purpose CMPs with multiple pre-defined voltage islands for power management. The CMPs are assumed to contain different classes of processing elements with multiple voltage/frequency execution modes to better cover a large range of applications. Task mapping is performed with awareness of both on-chip and off-chip memory traffic, and communication constraints such as the link and memory bandwidth. A novel mapping approach based on Extremal Optimization is proposed for large-scale CMPs. This new combinatorial optimization method has delivered very good results in quality and computational cost when compared to the classical simulated annealing., Peer Reviewed, Postprint (published version)

The complexity of large Chip Multiprocessors (CMP) makes design reuse a practical approach to reduce the manufacturing and design cost of high-performance systems. This paper proposes techniques for static task mapping onto general-purpose CMPs with multiple pre-defined voltage islands for power management. The CMPs are assumed to contain different classes of processing elements with multiple voltage/frequency execution modes to better cover a large range of applications. Task mapping is performed with awareness of both on-chip and off-chip memory traffic, and communication constraints such as the link and memory bandwidth. Besides proposing a linear programming model for small systems, a novel mapping approach based on Extremal Optimization is proposed for large-scale CMPs. This new combinatorial optimization method has delivered very good results in quality and computational cost when compared to the classical simulated annealing., Postprint (published version)

The architecture definition, design, and validation of the interconnect networks is a key step in the design of modern on-chip systems. This paper proposes a mathematical formulation of the problem of simultaneously defining the topology of the network and the message routes for the traffic among the processing elements of the system. The solution of the problem meets the physical and performance constraints defined by the designer. The method guarantees that the generated solution is deadlock free. It is also capable of automatically discovering topologies that have been previously used in industrial systems. The applicability of the method has been validated by solving realistic size interconnect networks modeling the typical multiprocessor systems., Peer Reviewed, Postprint (published version)