Congratulations @_Sartakov @LluisVilanova_ Munir Geden David Eyers @shina_en @ppietzuch https://t.co/Vf2Wfc9jP3

By LSDSImperial, 8 months 1 week ago

  • RT @ppietzuch: Existing distributed #reinforcement learning (RL) systems lack abstractions to distribute algorithms flexibly. Check out @LSDSImperial's work on #MSRL, an RL system that supports distribution polices for partitioning computation using dataflow graphs. https://t.co/ZKLWh9sbm3

    By LSDSImperial, 1 year 1 month ago

  • RT @SysML_ICL: 🚨 Announcing our exciting July Seminar line-up!
    Follow the links for details.

    📅 14/07: Davis Blalock will present his work "Multiplying Matrices Without Multiplying", ICML'21
    (1/3)
    https://t.co/AHUmZOEnBQ

    By LSDSImperial, 1 year 4 months ago

  • Please join us Thursday (9/6) at 2 pm BST for Girish Balakrishnan, IITM, talk "Succinct Data Structure for Path Graphs" https://t.co/C8y0UXkaoK

    By LSDSImperial, 1 year 5 months ago

  • Please join us Thursday (26/5) at 2 pm BST for Chi Wang, Microsoft Research, talk "Chi Wang, Microsoft Research" https://t.co/Gv3QPXVhS4

    By LSDSImperial, 1 year 6 months ago

  • Please join us Thursday (19/5) at 3:15pm BST for Peter Boncz, Vrije Universiteit Amsterdam, talk "FSST: fast random-access string compression" https://t.co/r9rOZZdxRT

    By LSDSImperial, 1 year 6 months ago

  • Please join us Thursday (19/5) at 2pm BST for Heming Cui, University of Hong Kong, talk "Building Four-dimensional Parallel Training Systems for Large AI Models" https://t.co/321J27Pk07

    By LSDSImperial, 1 year 6 months ago

  • Please join us Thursday (12/5) at 2pm BST for Luis Rodrigues, Universidade de Lisboa, talk "Kauri: BFT Consensus with Pipelined Tree-Based Dissemination and Aggregation" https://t.co/eBgnOWpxS8

    By LSDSImperial, 1 year 6 months ago

  • Please join us Thursday (28/4) at 2pm GMT for Jiwon Seo, Hanyang University, talk "Out-Of-Order BackProp: An Effective Scheduling Technique for Deep Learning" https://t.co/CY4RPNEpQ8

    By LSDSImperial, 1 year 7 months ago

  • RT @ppietzuch: Excited about OS kernels, hypervisors and low-level systems programming? Do you want to figure out how to make future cloud computing stacks more secure? At @LSDSImperial, we have fully-funded #PhD Studentships for international students. Apply here: https://t.co/zNZivRGn8X

    By LSDSImperial, 1 year 8 months 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
 BOSS
BOSS
A Bring-Your-Own-Kernel DBMS
Big Data Processing
 CloudCAP
CloudCAP
Compartments and Cloud-Native Applications
Cloud Computing
 Crossbow
Crossbow
Scalable Multi-GPU Deep Learning
Machine Learning
 Faasm
Faasm
High performance serverless computing
Big Data Processing, Serverless
 FractOS
FractOS
Secure and Efficient Disaggregated Systems
Cloud Computing, Systems Security
 KungFu
KungFu
Adaptive Distributed Machine Learning
Machine Learning
 LightSaber
LightSaber
Multi-core Window-Based Stream Processing
Big Data Processing
 Medea
Medea
Heterogenous Application Scheduling
Cloud Computing
 SGX-LKL
SGX-LKL
Linux Binaries in SGX Enclaves
Systems Security
 Teechain
Teechain
A Secure Blockchain Payment Network
Systems Security

Recent Publications

MSRL: Distributed Reinforcement Learning with Dataflow Fragments
H. Zhu; B. Zhao; G. Chen; W. Chen; Y. Chen; S. Liang; Y. Yang; P. Pietzuch; and L. Chen

In USENIX ATC'23

Translation Pass-Through for Near-Native Paging Performance in VMs
S. Bergman; M. Silberstein; T. Shinagawa; P. Pietzuch; and L. Vilanova

In USENIX ATC'23

ORC: Increasing Cloud Memory Density via Object Reuse with Capabilities
V. Sartakov; L. Vilanova; M. Geden; D. Eyers; T. Shinagawa; and P. Pietzuch

In USENIX OSDI'23

Scabbard: Single Node Fault-Tolerant Stream Processing
G. Theodorakis; F. Kounelis; P. Pietzuch; and H. Pirk

In VLDB'22

More Publications

The LSDS Group

 Marios Kogias
Marios Kogias
Assistant Professor
Peter Pietzuch
Peter Pietzuch
Professor
Holger Pirk
Holger Pirk
Associate Professor
Lluís Vilanova
Lluís Vilanova
Associate Professor
Andrea Piermarteri
Andrea Piermarteri
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
Michael Paper
Michael Paper
Research Assistant
Konstantinos Fertakis
Konstantinos Fertakis
PhD Student
Ahmad Khazale
Ahmad Khazale
PhD Student
Fotis Kounelis
Fotis Kounelis
PhD Student
Eleftheria Mappoura
Eleftheria Mappoura
PhD Student
Domagoj Margan
Domagoj Margan
PhD Student
Carlos Segarra
Carlos Segarra
PhD Student
Jinnan Guo
Jinnan Guo
PhD Student
Alessandro Fogli
Alessandro Fogli
PhD Student
Pedro Silvestre
Pedro Silvestre
PhD Student
Marcel Wagenländer
Marcel Wagenländer
PhD Student
David Loughlin
David Loughlin
PhD Student
Hubert Mohr-Daurat
Hubert Mohr-Daurat
PhD Student
Takahiro Shinagawa
Takahiro Shinagawa
Visitor
Jack Pearce
Jack Pearce
Research Assistant

Open Positions

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.

Read More
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