The Gendered Gaze: Torrellas' Sadistic "Martyrdom" in "Grisel y Mirabella"

Autor: GONZÁLEZ, LUIS F. LÓPEZ

Publikováno v: Revista Canadiense de Estudios Hispánicos, 2017 Jan 01. 41(2), 349-372.

Externí odkaz: http://www.jstor.org/stable/26310063

Chameleon: Adaptive Caching and Scheduling for Many-Adapter LLM Inference Environments

Autor: Iliakopoulou, Nikoleta, Stojkovic, Jovan, Alverti, Chloe, Xu, Tianyin, Franke, Hubertus, Torrellas, Josep

The widespread adoption of LLMs has driven an exponential rise in their deployment, imposing substantial demands on inference clusters. These clusters must handle numerous concurrent queries for different LLM downstream tasks. To handle multi-task se

Externí odkaz: http://arxiv.org/abs/2411.17741

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DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

Autor: Stojkovic, Jovan, Zhang, Chaojie, Goiri, Íñigo, Torrellas, Josep, Choukse, Esha

The rapid evolution and widespread adoption of generative large language models (LLMs) have made them a pivotal workload in various applications. Today, LLM inference clusters receive a large number of queries with strict Service Level Objectives (SL

Externí odkaz: http://arxiv.org/abs/2408.00741

Last-Level Cache Side-Channel Attacks Are Feasible in the Modern Public Cloud (Extended Version)

Autor: Zhao, Zirui Neil, Morrison, Adam, Fletcher, Christopher W., Torrellas, Josep

Publikováno v: 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2024), Volume 2, pages 582-600, La Jolla, CA, USA, May 2024

Last-level cache side-channel attacks have been mostly demonstrated in highly-controlled, quiescent local environments. Hence, it is unclear whether such attacks are feasible in a production cloud environment. In the cloud, side channels are flooded

Externí odkaz: http://arxiv.org/abs/2405.12469