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Many-core co-design is a complex task in which application complexity designspace, heterogeneous many-core architecture design space, parallel programminglanguage design space, simulator design space and optimizer design space shouldget integrated through a binding process and these design spaces, an ensembleof what is called many-core co-design spaces. It is indispensable to build aco-design automation process to dominate over the co-design complexity to cutdown the turnaround time. The co-design automation is frame worked tocomprehend the dependencies across the many-core co-design spaces and devisethe logic behind these interdependencies using a set of algorithms. Thesoftware modules of these algorithms and the rest from the many-core co-designspaces interact to crop up the power-performance optimized heterogeneousmany-core architecture specific for the simultaneous execution of coapplications without space-time sharing. It is essential that such co-designautomation has a built-in user-customizable workload generator to benchmark theemerging many-core architecture. This customizability benefits the generationof complex workloads with the desired computation complexity, communicationcomplexity, control flow complexity, and locality of reference, specified undera distribution and established on quantitative models. In addition, thecustomizable workload model aids the generation of what is called computationaland communication surges. None of the current day benchmark suites encompassesapplications and kernels that can match the attributes of customizable workloadmodel proposed in this paper. Aforementioned concepts are exemplified in, thecase study supported by simulation results gathered from the simulator.

Consolidating the innovative concepts towards Exascale computing for  Co-Design of Co-Applications ll: Co-Design Automation - Workload  Characterization