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Gal Shalom

dblp:314/7077 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0002-1636-7531ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 64% Interconnection networks and networks-on-chip · 19% Reconfigurable computing and FPGAs · 13%
Computer networks
1 paper
Datacenter networks · 100%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › virtualization
device pass-through
0.912025
Device-Assisted Live Migration of RDMA Devices · SOSP 2025
Cloud and datacenter computing › virtualization › virtual machine migration
live migration
0.912025
Device-Assisted Live Migration of RDMA Devices · SOSP 2025
Interconnection networks and networks-on-chip
remote direct memory access
0.912025
Device-Assisted Live Migration of RDMA Devices · SOSP 2025
Cloud and datacenter computing
virtualization
0.912025
Device-Assisted Live Migration of RDMA Devices · SOSP 2025
Datacenter networks
RDMA
0.612022
FlexDriver: a network driver for your accelerator · ASPLOS 2022
Reconfigurable computing and FPGAs
FPGA accelerator
0.612022
FlexDriver: a network driver for your accelerator · ASPLOS 2022
Cloud and datacenter computing
cloud infrastructure
0.312025
Device-Assisted Live Migration of RDMA Devices · SOSP 2025
Memory systems
memory disaggregation
0.212022
FlexDriver: a network driver for your accelerator · ASPLOS 2022

Methods — techniques the papers use, named apart from their topics

load/store interface · 1.1NIC control structure compression · 1.1
YearPublicationVenuePosition
2025 Device-Assisted Live Migration of RDMA Devices
abstract
Recently, we have seen growing pressure to move highperformance workloads, such as HPC and AI, to cloud environments that offer more affordable and manageable infrastructure. These workloads require direct access to RDMA devices for high-performance communication. Device passthrough, however, violates the decoupling between the guest OS and the underlying hardware, making Live Migration (LM) extremely challenging [29, 38, 40, 42, 48].
Artem Y. Polyakov, Gal Shalom, Asaf Schwartz, Aviad Yehezkel, Omri Ben David, Omri Kahalon, Ariel Shahar, Liran Liss
SOSP2
2022 FlexDriver: a network driver for your accelerator
abstract
We propose a new system design for connecting hardware and FPGA accelerators to the network, allowing them to directly control commodity ASIC NICs without using the CPU. This solves the key challenge of leveraging existing NIC hardware offloads such as RDMA and virtualization for hardware disaggregation and accelerator networking. Our approach supports a diverse set of use cases, from direct network access for disaggregated accelerators to inline acceleration of the network stack and disaggregation of main system memory, all without implementing complex networking logic. To demonstrate this approach, we build FlexDriver (FLD) , a hardware module that implements a NIC data-plane driver. Our main technical contribution is compressing NIC control structures by \(5\times\) , allowing FLD to achieve high scalability with low die area and no memory bandwidth interference. We build two prototypes – FLD core on NVIDIA Innova-2 FPGA SmartNICs and FLD with a load/store interface on IBM OpenCAPI FPGA deployment with ConnectX-6 Dx. We demonstrate four different use cases: a disaggregated LTE cipher, an IP-reassembly inline accelerator, an IoT cryptographic-token authentication offload, and a fine-grained memory disaggregation datapath over RDMA. These leverage the ASIC NIC for RDMA processing, VXLAN tunneling, and traffic shaping, without CPU involvement.
Haggai Eran, Maxim Fudim, Gabi Malka, Gal Shalom, Noam Cohen, Amit Hermony, Dotan Levi, Liran Liss, Mark Silberstein
ASPLOS4