Fast and Cycle-Accurate Emulation of Large-Scale Networks-on-Chip Using a Single FPGA

Modeling and simulation/emulation play a major role in research and development of novel Networks-on-Chip (NoCs). However, conventional software simulators are so slow that studying NoCs for emerging many-core systems with hundreds to thousands of cores is challenging. State-of-the-art FPGA-based NoC emulators have shown great potential in speeding up the NoC simulation, but they cannot emulate large-scale NoCs due to the FPGA capacity constraints. Moreover, emulating large-scale NoCs under synthetic workloads on FPGAs typically requires a large amount of memory and thus involves the use of off-chip memory, which makes the overall design much more complicated and may substantially degrade the emulation speed. This article presents methods for fast and cycle-accurate emulation of NoCs with up to thousands of nodes using a single FPGA. We first describe how to emulate a NoC under a synthetic workload using only FPGA on-chip memory (BRAMs). We next present a novel use of time-division multiplexing where BRAMs are effectively used for emulating a network using a small number of nodes, thereby overcoming the FPGA capacity constraints. We propose methods for emulating both direct and indirect networks, focusing on the commonly used meshes and fat-trees ( k -ary n -trees). This is different from prior work that considers only direct networks. Using the proposed methods, we build a NoC emulator, called FNoC, and demonstrate the emulation of some mesh-based and fat-tree-based NoCs with canonical router architectures. Our evaluation results show that (1) the size of the largest NoC that can be emulated depends on only the FPGA on-chip memory capacity; (2) a mesh-based NoC with 16,384 nodes (128×128 NoC) and a fat-tree-based NoC with 6,144 switch nodes and 4,096 terminal nodes (4-ary 6-tree NoC) can be emulated using a single Virtex-7 FPGA; and (3) when emulating these two NoCs, we achieve, respectively, 5,047× and 232× speedups over BookSim, one of the most widely used software-based NoC simulators, while maintaining the same level of accuracy.