Concept

Hardware-assisted virtualization

Related publications (59)

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Ali Pahlevan

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

2024

A RISC-V Extension to Minimize Privileges of Enclave Runtimes

Edouard Bugnion, Neelu Shivprakash Kalani

In confidential computing, the view of the system software is Manichean: the host operating system is untrusted and the TEE runtime system is fully trusted. However, the runtime system is often as complex as a full operating system, and thus is not free fr ...

ACM2023

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

Alexandre Schmid, Lizeth Gonzalez Carabarin

Model compression techniques have lead to a reduction of size and number of computations of Deep Learning models. However, techniques such as pruning mostly lack of a real co-optimization with hardware platforms. For instance, implementing unstructured pru ...

IEEE2022

Design of a Collimation Section for the FCC-ee

Tatiana Pieloni, Bruce Roderik, Frank Zimmermann

The design parameters of the FCC-ee foresee operation with a total stored beam energy of about 20 MJ, exceeding those of previous lepton colliders by almost two orders of magnitude. Given the inherent damage potential, a halo collimation system is studied ...

JACoW Publishing2022

Performance Characterization of HTAP Workloads

Anastasia Ailamaki, Sandhya Dwarkadas, Utku Sirin

Hybrid Transactional and Analytical Processing (HTAP) systems have become popular in the past decade. HTAP systems allow running transactional and analytical processing workloads on the same data and hardware. As a result, they suffer from workload interfe ...

IEEE COMPUTER SOC2021

JIT works: decide when all data is known (VLDB Women in Database Research Award talk)

Anastasia Ailamaki

When the time comes to make a critical decision, it is of paramount importance to prepare enough so that all the information necessary is available at decision time. Under-preparation leads to uninformed decisions; over-preparation, however, may lead to co ...

ASSOC COMPUTING MACHINERY2020

Micro-architectural Analysis of OLAP: Limitations and Opportunities

Anastasia Ailamaki, Utku Sirin

Understanding micro-architectural behavior is important for efficiently using hardware resources. Recent work has shown that in-memory online transaction processing (OLTP) systems severely underutilize their core micro-architecture resources [29]. Whereas, ...

ASSOC COMPUTING MACHINERY2020

WOK: Statistical Program Slicing in Production

James Richard Larus, Bogdan-Alexandru Stoica

Dynamic program slicing can significantly reduce the amount of code developers need to inspect by focusing only on program statements relevant to their investigation. However, this technique is still not ready for production-level use either in terms of ru ...

IEEE2019

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

David Atienza Alonso, Marina Zapater Sancho, Ali Pahlevan, Xiaoyu Qu

Modern cloud data centers (DCs) need to tackle efficiently the increasing demand for computing resources and address the energy efficiency challenge. Therefore, it is essential to develop resource provisioning policies that are aware of virtual machine (VM ...

2018

Decoder Partitioning: Towards Practical List Decoding of Polar Codes

Rüdiger Urbanke, Seyed Hamed Hassani, Marco Mondelli

Polar codes represent one of the major recent breakthroughs in coding theory and, because of their attractive features, they have been selected for the incoming SG standard. As such, a lot of attention has been devoted to the development of decoding algori ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

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