Uncovering Real GPU NoC Characteristics: Implications on Interconnect Architecture

Abstract

A critical component of high-throughput processors such as GPUs is the network-on-chip (NoC) that interconnects the large number of cores and the memory partitions together. In this work, we provide a detailed analysis, in terms of latency and bandwidth, of real GPU NoC across several generations of modern NVIDIA GPUs. Our analysis identifies how non-uniform latency exists between the cores and the memory partitions based on their physical location in the GPU. The non-uniformity can result in up to approximately 70 % difference in on-chip latency. In comparison, the bandwidth provided from the cores to the memory partitions is approximately uniform. However, recent GPUs that consist of multiple GPU “partitions” present different on-chip latency and bandwidth characteristics when communicating between the partitions. Based on our analysis of real GPU interconnect, we discuss potential implications including its impact on timing used in side-channel attacks as well as NoC microarchitectures. We show how the non-uniform latency can be exploited in a timing side-channel attack within a GPU as the core location impacts performance (or timing). In addition, proper understanding (and proper assumptions) of GPU NoC is critical to ensure a network that does not bottleneck the overall system performance.