5 citations · 14 across the 6 of their papers we have counts for
6 papers
Transfer-Learning-Based Autotuning Using Gaussian Copula
Thomas Randall, Jaehoon Koo, Brice Videau +6
As diverse high-performance computing (HPC) systems are built, many opportunities arise for applications to solve larger problems than ever before. Given the significantly increase…
Enhancing Virtual Distillation with Circuit Cutting for Quantum Error Mitigation
Peiyi Li, Ji Liu, Hrushikesh Pramod Patil +2
Virtual distillation is a technique that aims to mitigate errors in noisy quantum computers. It works by preparing multiple copies of a noisy quantum state, bridging them through a…
Efficient precision simulation of processes with many-jet final states at the LHC
Enrico Bothmann, Taylor Childers, Christian Guetschow +5
We present a scalable technique for the simulation of collider events with multi-jet final states, based on an improved parton-level event file format. The method is implemented fo…
Understanding Automatic Differentiation Pitfalls
Jan Hückelheim, Harshitha Menon, William Moses +3
Automatic differentiation, also known as backpropagation, AD, autodiff, or algorithmic differentiation, is a popular technique for computing derivatives of computer programs accura…
Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis
Ji Liu, Ed Younis, Mathias Weiden +3
We propose a novel hierarchical qubit mapping and routing algorithm. First, a circuit is decomposed into blocks that span an identical number of qubits. In the second stage permuta…
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales
Xingfu Wu, Prasanna Balaprakash, Michael Kruse +7
As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical…