10 citations · 17 across the 6 of their papers we have counts for
6 papers
Cost-aware Duration Prediction for Software Upgrades in Datacenters
Yi Ding, Aijia Gao, Thibaud Ryden +4
Software upgrades are critical to maintaining server reliability in datacenters. While job duration prediction and scheduling have been extensively studied, the unique challenges p…
Navigating the dynamic noise landscape of variational quantum algorithms with QISMET
Gokul Subramanian Ravi, Kaitlin N. Smith, Jonathan M. Baker +5
Transient errors from the dynamic NISQ noise landscape are challenging to comprehend and are especially detrimental to classes of applications that are iterative and/or long-runnin…
SCOPE: Safe Exploration for Dynamic Computer Systems Optimization
Hyunji Kim, Ahsan Pervaiz, Henry Hoffmann +2
Modern computer systems need to execute under strict safety constraints (e.g., a power limit), but doing so often conflicts with their ability to deliver high performance (i.e. min…
Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression
Yi Ding, Alex Renda, Ahsan Pervaiz +2
Sample-efficient machine learning (SEML) has been widely applied to find optimal latency and power tradeoffs for configurable computer systems. Instead of randomly sampling from th…
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction
Yi Ding, Avinash Rao, Hyebin Song +2
Datacenters execute large computational jobs, which are composed of smaller tasks. A job completes when all its tasks finish, so stragglers -- rare, yet extremely slow tasks -- are…
CAFQA: A classical simulation bootstrap for variational quantum algorithms
Gokul Subramanian Ravi, Pranav Gokhale, Yi Ding +7
This work tackles the problem of finding a good ansatz initialization for Variational Quantum Algorithms (VQAs), by proposing CAFQA, a Clifford Ansatz For Quantum Accuracy. The CAF…