With increasing communication demands of processor and memory cores in Systems on Chips (SoCs), scalable Networks on Chips (NoCs) are needed to interconnect the cores. For the use of NoCs to be feasible in today's industrial designs, a custom-tailored, application-specific NoC that satisfies the design objectives and constraints of the targeted application domain is required. In this work, we present a design methodology that automates the synthesis of such application-specific NoC architectures. We present a floorplan aware design method that considers the wiring complexity of the NoC during the topology synthesis process. This leads to detecting timing violations on the NoC links early in the design cycle and to have accurate power estimations of the interconnect. We incorporate mechanisms to prevent deadlocks during routing, which is critical for proper operation of NoCs. We integrate the NoC synthesis method with an existing design flow, automating NoC synthesis, generation, simulation and physical design processes. We also present ways to ensure design convergence across the levels. Experiments on several SoC benchmarks are presented, which show that the synthesized topologies provide a large reduction in network power consumption (2.78× on average) and improvement in performance (1.59× on average) over the best mesh and mesh-based custom topologies. An actual layout of a multimedia SoC with the NoC designed using our methodology is presented, which shows that the designed NoC supports the required frequency of operation (close to 900 MHz) without any timing violations. We could design the NoC from input specifications to layout in 4 hours, a process that usually takes several weeks.

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ScratchPad Memories (SPMs) are commonly used in embedded systems because they are more energy-efficient than caches and enable tighter application control on the memory hierarchy. Optimally mapping code and data to SPMs is, however, still a challenge. This paper proposes an optimal scratchpad mapping approach for code segments, which has the distinctive characteristic of working directly on application binaries, thus requiring no access to either the compiler or the application source code -a clear advantage for legacy or proprietary, IP-protected applications.The mapping problem is solved by means of a Dynamic Programming algorithm applied to the execution traces of the target application. The algorithm is able to find the optimal set of instructions blocks to be moved into a dedicated SPM, either minimizing energy consumption or execution times. A patching tool, which can use the output of the optimal mapper, modifies the binary of the application and moves the relevant portions of its code segments to memory locations inside of the SPM.