@raulcfernandez Not yet, but it will be available after shepherding.

By LSDSImperial, 1 week 2 days ago

  • RT @ppietzuch: It's great news to get at the end of a long day that our paper on #CublicleOS, a library OS with practical hardware-backed c…

    By LSDSImperial, 1 week 2 days ago

  • Please join us Thursday (19/11) at 2pm UTC for Dr Joy Arulraj, Georgia Institute of Technology, online talk "Data Management on Non-Volatile Memory" https://t.co/jhSBzrL8CD

    By LSDSImperial, 1 week 5 days ago

  • Please join us Thursday (12/11) at 2pm UTC for Dr Martin Hentschel & Dr Max Heimel, Snowflake, online talk "A Peek into Snowflake's Scalable Architecture" https://t.co/nDYW1H3qZ4

    By LSDSImperial, 2 weeks 5 days ago

  • Please join us Thursday (5/11) at 2pm UTC for Marios Kogias', Microsoft Research Cambridge, online talk "Making RPCs first class datacenter citizens" https://t.co/w7Y3TOFv7j

    By LSDSImperial, 3 weeks 3 days ago

  • Please join us Thursday (29/10) at 2pm GMT for Jo Van Bulck's, KU Leuven, online talk "Microarchitectural side-channel attacks for untrusted operating systems" https://t.co/heiqOwD9kA

    By LSDSImperial, 1 month 2 days ago

  • Please join us tomorrow (21/10) at 2pm BST for Niv Dayan, Pliops, online talk "Scaling Storage Engines" https://t.co/egNma7SADf

    By LSDSImperial, 1 month 1 week ago

  • RT @ppietzuch: I'm excited that our paper on #KungFu, a distributed deep learning library that adapts the training process at runtime was a…

    By LSDSImperial, 3 months 1 week ago

  • @raulcfernandez The memory safety guarantees of WebAssembly allow us to isolate many functions as part of a single address, while efficiently sharing state between them. We evaluate with ML training/inference and also support Python due to Faasm's POSIX interface.

    By LSDSImperial, 7 months 5 days ago

  • RT @ppietzuch: Our work on #Faasm, a high-density stateful serverless runtime based on WebAssembly was accepted at @usenix #ATC2020. Check…

    By LSDSImperial, 7 months 5 days ago
More tweets

The goal of the LSDS group is to support the design and implementation of tomorrow's large-scale data-intensive systems. We investigate new abstractions and infrastructures for building scalable, robust and secure data-intensive applications.

Current Projects

  • View All
  • Big Data Processing
  • Serverless
  • Cloud Computing
  • Systems Security
  • Machine Learning
  • Networking
 Crossbow
Crossbow
Scalable Multi-GPU Deep Learning
Machine Learning
 Faasm
Faasm
Serverless Big Data Runtime
Big Data Processing, Serverless
 KungFu
KungFu
Adaptive Distributed Machine Learning
Machine Learning
 LightSaber
LightSaber
Multi-core Window-Based Stream Processing
Big Data Processing
 MDF
MDF
Meta-Dataflows
Big Data Processing
 Medea
Medea
Heterogenous Application Scheduling
Cloud Computing
 SABER
SABER
Hybrid Stream Processing
Big Data Processing, Machine Learning
 SEEP
SEEP
Stateful Big Data Processing
Big Data Processing
 SERECA
SERECA
Hardware-Assisted Cloud Security
Cloud Computing, Systems Security
 SGX-LKL
SGX-LKL
Linux Binaries in SGX Enclaves
Systems Security
 Teechain
Teechain
A Secure Blockchain Payment Network
Systems Security

Recent Publications

CubicleOS: A Library OS with Software Componentisation for Practical Isolation
V.A. Sartakov; L. Vilanova; and P. Pietzuch

In ACM ASPLOS'21

KungFu: Making Training in Distributed Machine Learning Adaptive
L. Mai; G. Li; M. Wagenländer; K. Fertakis; A.O. Brabete; and P. Pietzuch

In USENIX OSDI'20

Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources
M. Wagenländer; L. Mai; G. Li; and P. Pietzuch

In USENIX Hotcloud'20

Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing
S. Shillaker; and P. Pietzuch

In USENIX ATC'20

More Publications

Upcoming Events

Title To Be Confirmed
Daniel J Abadi
University of Maryland
Thursday, 3 December 2020 - 2:00pm, Online
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The LSDS Group

 Peter Pietzuch
Peter Pietzuch
Professor
Holger Pirk
Holger Pirk
Lecturer (Assistant Professor)
Daphne Tuncer
Daphne Tuncer
Imperial College Research Fellow
Shujie Cui
Shujie Cui
Post-doctoral Researcher
Luo Mai
Luo Mai
Post-doctoral Researcher
Vasily A. Sartakov
Vasily A. Sartakov
Post-doctoral Researcher
Huanzhou Zhu
Huanzhou Zhu
Post-doctoral Researcher
Guo Li
Guo Li
Research Assistant
Konstantinos Fertakis
Konstantinos Fertakis
PhD Student
Ahmad Khazale
Ahmad Khazale
PhD Student
Fotis Kounelis
Fotis Kounelis
PhD Student
Domagoj Margan
Domagoj Margan
PhD Student
Carlos Segarra
Carlos Segarra
PhD Student
Alex Shamis
Alex Shamis
PhD Student
Simon Shillaker
Simon Shillaker
PhD Student
Georgios Theodorakis
Georgios Theodorakis
PhD Student
Marcel Wagenlander
Marcel Wagenlander
Visitor

Open Positions

Post-Doctoral Researcher
In Systems Security
 

Join the EU-funded SecureCloud project and investigate how new hardware trust mechanisms can be used to improve the security of cloud computing applications.

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Post-Doctoral Researcher
In Distributed Systems, Systems, Databases
 

Multiple post-doctoral positions available in the areas of distributed systems, databases, and networking.

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PhD position
In Computer Systems for BigData and Data Science
 

Two PhD positions are available in the broad area of Computer Systems with focus on designing and building systems that support BigData and Data Science workloads on modern and future hardware platforms.

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PhD position
In Big Data Management: Auto-tuning for modern hardware
 

PhD position in Big Data Management with focus on Auto-tuning for modern hardware under the supervision of Dr. Holger Pirk.

Read More
PhD position
In in Big Data Management: Data Compression
 

PhD position in Big Data Management with focus on Data Compression under the supervision of Dr. Holger Pirk.

Read More

Interested in joining LSDS? How to apply