Tootfinder

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning
Djamel Rassem Lamouri, Iheb Nassim Aouadj, Smail Kourta, Riyadh Baghdadi
https://arxiv.org/abs/2506.01880

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning
Compilers are crucial in optimizing programs and accelerating their execution. However, optimizing programs automatically using compilers is not trivial. Recent work has attempted to use reinforcement learning (RL) to solve this problem. It has limitations though. Current methods either do not support the optimization of general loop nests or can only be used to optimize loop nests seen during training. In this paper, we propose Pearl, a novel framework that uses deep reinforcement learning to …

Relay Selection and User Equipment Admission in Resource-Efficient NextG Sidelink Communications
Yalin E. Sagduyu, Tugba Erpek, Sastry Kompella, Kemal Davaslioglu
https://arxiv.org/abs/2506.03328

Relay Selection and User Equipment Admission in Resource-Efficient NextG Sidelink Communications
5G/6G sidelink communications addresses the challenge of connecting outer UEs, which are unable to directly access a base station (gNodeB), through inner UEs that act as relays to connect to the gNodeB. The key performance indicators include the achievable rates, the number of outer UEs that can connect to a gNodeB, and the latency experienced by outer UEs in establishing connections. We consider problem of determining the assignment of outer UEs to inner UEs based on the channel, interference,…

Does anyone who uses nasal pillows find they get pressure on the septum? Sometimes it can get quite uncomfortable and tonight it's been bad enough to have to take the mask off and could be what's wakened me. Other nights it's not such a problem. Is this a known issue? I'm not aware that I have a particularly huge septum 😄 Mask is a small. #cpap

Sharp error bounds for approximate eigenvalues and singular values from subspace methods
Irina-Beatrice Haas, Yuji Nakatsukasa
https://arxiv.org/abs/2506.01207

Sharp error bounds for approximate eigenvalues and singular values from subspace methods
Subspace methods are commonly used for finding approximate eigenvalues and singular values of large-scale matrices. Once a subspace is found, the Rayleigh-Ritz method (for symmetric eigenvalue problems) and Petrov-Galerkin projection (for singular values) are the de facto method for extraction of eigenvalues and singular values. In this work we derive quadratic error bounds for approximate eigenvalues obtained via the Rayleigh-Ritz process. Our bounds take advantage of the fact that extremal ei…