# PCCNoC: Packet Connected Circuit as Network on Chip for High Throughput and Low Latency SoCs
## 5 Implementation and Evaluation
### Latency and Throughput
The throughput saturation points are 24, 32, 40, and 56 packets in a transmission, respectively, for 4 \(\times\) 4 PS NoC, 6 \(\times\) 6 PS NoC, 8 \(\times\) 8 PS NoC, and PCCNOC. As the packet number increases, the average throughput of PCCNoC keeps increasing and its average latency remains basically unchanged. The throughput of PCCNoC improves 115%, 169%, 242% and the latency decreases 96%, 97%, 97% respectively compared with 4 \(\times\) 4, 6 \(\times\) 6 and 8 \(\times\) 8 PS NoC for transmission task with 100 packets (400 bytes). Because each packet for PS NoC needs to be routed, when there are more packets to transmit there is a higher risk of router congestion. In PCCNoC, however, the data payload is transmitted on a locked circuit, and all packet-related drawbacks disappear. With the increase in Transmission length, the delay of PCCNoC tends to flatten out, while the network throughput increases greatly. Thanks to the fast, low-delay, and high-throughput circuit switching after the datapath is locked, PCCNoC is suitable for heterozygeous multi-core real-time SOC. If the interface bit width is set to 256 bits in real application scenarios, the improvement is even more obvious. Simple traffic models such as uniform random are useful for NoC designers in acquiring insights by stressing the network with a regular predictable traffic pattern. However, they do not represent realistic traffic loads, which are necessary to assess NoCs [41]. Thus, utilizing traffic models that mimic realistic traffic behaviour, such as CTG-based and Rent's rule, is significantly important. CTG-based traffic injects packets according to the traffic rate between each communication node in the task graphs generated by FTTG [42]. Rent's rule uses communication probability matrix to send packets to each node uniformly, obtain synthesis flows, realize the communication locality [43]. Our experiments were designed to trace NoC behaviour under different traffic models with an 8 \(\times\) 8 mesh NoC using Noxim. Figure 14 depicts the average latency according to the injection rate in an 8 \(\times\) 8 mesh NoC. The performance of PCCNOC was examined with VCS [7], MRBS [9], MRCN [8], and SmartFork [14]. It can be seen that the saturation point of injection rate for PCCNoC is higher than all other related work, and the average latency is lower at injection rates from 0.005 to 0.065 for the all three test cases. For the injection rate at 0.04, the average latency reduction achieved by PCCNoC is 59%, 58%, 72%, 62%, and 93% in comparison to Smartfork, HOECP, MRBS, MRCN and VCS, respectively. Figure 13: Comparison of (**a**) average latency and (**b**) average throughput for different NoC with different flip numbers. Next, we focus our attention on real benchmark traffic. Snipersim 6.1 [44] was used to trace real benchmark traffic, and the router and network interface of PCCNOC were implemented on Snipersim. We selected five PARSEC [45] benchmark applications (viz. vips, X264, fluidanimate, blackscholes, and dedup) due to their variability in offering both communication and computation-intensive workload. The performance of the proposed technique was examined against a baseline packet switching NoC (namely, PS) and two similar works: Dancyflyer [15], which supports selection of multipath output port under dynamic path selection policy, and VCS [7], which reserves a virtual path for routing packets in an adaptive mode for each communication flow. Both methods support in-order packet delivery. The simulation was executed on an 8 \(\times\) 8 mesh NoC and the execution time was 100,000 cycles. In the case of PARSEC benchmark application, the maximum gain in terms of average throughput achieved by three techniques is observed as 42%, 35%, and 23% for PCCNOC, VCS, and Dancerfly, respectively, compared with the baseline (see Figure 15).