Multicube Explorer: An Open Source Framework for Design Space Exploration of Chip Multi-Processors
Zaccaria V., Palermo G., Castro F., Silvano C., Mariani G.
Contributo in atti di conferenza
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
Atti di conferenza
2PARMA: Proceedings of the Workshop on Parallel Programming and Run-time Management Techniques for Many-core Architectures