Team

Academic Members

Mark Silberstein, Associate Professor

Research Interests:

Computer Systems, Operating Systems, Compute and I/O Accelerator, Hardware security and side channels, GPGPU and FPGA computing, Trusted Execution Environments, Programmable Networks

Staff

Pavel Lifshits, Leading Engineer

Systems Software and OS
GPUs
Trusted execution environment
Signal processing
Power side channels

Bella Shavit, Research Coordinator

Graduate Students

M.Sc

Ori Ben Zur

Assaf Klein

Leonid Dyachkov

Ph.D

Jakob Krebs

Alon Rashelbach

Computational approach to network packet classification

Lior Zeno

Programmable networks

Post Docs

Noga H. Rotman

Research Interests:

Networking, Systems and Security, Machine Learning, Data and exciting datasets

Alumni

Ron Marcus

2023

Now at:

PliOPS

Igor De-Paula

2023

Now at:

Cisco

Lev Rosenblit

Security analysis of GPUs

Now at:

RingCentral

Shai Bergman

2022, Ph.D

Architectural and OS support for disaggregated memory
OS Integration of peer-to-peer transfers between GPUs and SSDs

Haggai Eran

2022

OS abstractions for programmable SmartNICs
Data center network congestion control

Now at:

NVIDIA Networking

Alon Berkenstadt

2022

Now at:

Hailo

Lina Maudlej

2021

SmartNIC-based access to devices in disaggregated systems
Accelerator-centric operating system

Now at:

SpeeData

Meni Orenbach

2021

OS abstractions for trusted execution environments
Controlled side channel mitigations for SGX

Now at:

NVIDIA Research

Gabi Malka

2021, Engineer

FPGA development
FPGA-based SmartNICs

Menachem Adelman

2021

Accelerating DNN training via tensor product approximation

Lluis Vilanova

2020, Post Doc

An OS for disaggregated data centers

Now at:

Imperial College London

Maroun Tork

2019, MSc

SmartNIC-driven accelerator-centric network servers

Now at:

Facebook

Tanya Brokhman

Thesis

2019, MSc

A unified page cache in heterogeneous systems

Now at:

Network.IO Innovation Lab

Marina Minkin

Thesis

2019

Speculative execution attacks on SGX enclaves

Now at:

University of Michigan

Vasilis Dimitsas

2018, MSc

I/O prefetcher for GPUs

Now at:

Graphcore

Shai Vaknin

2018, M.Sc

Dynamic update of learning rate in DNN training

Now at:

Facebook

Amir Wated

2018, MSc

Design of GPU-centric network servers
Native support for efficient GPU-side networking

Now at:

Cisco

Feras Daoud

2017, M.Sc.

GPURDMA: high performance network I/O on GPUs

Now at:

Mellanox

Sagi Shahar

2016, MSc

Efficient file I/O from GPUs
Software-managed virtual memory in GPUs

Now at:

Google

Matan Hamilis

Thesis

2015, MSc

High performance additive FFT in finite fields

Now at:

IDF