  The development of fault-tolerant quantum computers (FTQCs) is gaining
increased attention within the quantum computing community. Like their digital
counterparts, FTQCs, equipped with error correction and large qubit numbers,
promise to solve some of humanity's grand challenges. Estimates of the resource
requirements for future FTQC systems are essential to making design choices and
prioritizing R&D efforts to develop critical technologies. Here, we present a
resource estimation framework and software tool that estimates the physical
resources required to execute specific quantum algorithms, compiled into their
graph-state form, and laid out onto a modular superconducting hardware
architecture. This tool can predict the size, power consumption, and execution
time of these algorithms at as they approach utility-scale according to
explicit assumptions about the system's physical layout, thermal load, and
modular connectivity. We use this tool to study the total resources on a
proposed modular architecture and the impact of tradeoffs between and
inter-module connectivity, latency and resource requirements.
