Virtuoso: High Resource Utilization and {\mu}s-scale Performance Isolation in a Shared Virtual Machine TCP Network Stack

Virtualization improves resource efficiency and ensures security and performance isolation for cloud applications. To that end, operators today use a layered architecture that runs a separate network stack instance in each VM and container connected to a separate virtual switch. Decoupling through layering reduces complexity, but induces performance and resource overheads that are at odds with increasing demands for network bandwidth, communication requirements for large distributed applications, and low latency. We present Virtuoso, a new software networking stack for VMs and containers. Virtuoso performs a fundamental re-organization of the networking stack to maximize CPU utilization, enforce isolation, and minimize networking stack overheads. We maximize utilization by running one elastically shared network stack instance on dedicated cores; we enforce isolation by performing central and fine-grained per-packet resource accounting and scheduling; we reduce overheads by building a single-layer data path with a one-shot fast-path incorporating all processing from the TCP transport layer through network virtualization and virtual switching. Virtuoso improves resource utilization by up to 50%, latencies by up to 42% compared to other virtualized network stacks without sacrificing isolation, and keeps processing overhead within 11.5% of unvirtualized network stacks.Comment: Under submission for conference peer revie

Solving the quantum simulation problem via signal analysis

The computation of scattering amplitudes soon becomes an intractable problem for a classical computer as the size of the quantum system and the evolution time grows. Nevertheless, this problem is in the class BQP, where a quantum computer can offer an efficient solution in time polynomial in both the system size and evolution time. The currently available quantum devices (NISQ) have enough qubits to represent challenging instances of this problem. However, because of errors, they can not run the simulations for long times. Our research frames the quantum simulation problem as a signal analysis one to combine NISQ devices' power and classical computation. The goal is to devise an algorithm that can forecast the expectation values at longer times with bounded error, given the outcome of short-time simulations. Using a Matrix Pencil approach, we conduct numerical experiments that suggest that the predictions can be accurate under certain conditions. At the same time, we are aware of adversarial problem instances that can make the prediction hard