Igor Smolyar

dblp:137/0885 · DBLP profile ↗
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5ranked-venue papers
2as first author
2since 2021 · last 2022
—ORCID · none

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

Systems, architecture and hardware · 3 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 3 · 1 first-author · 1 since 2021Security and privacy · 1 · 1 first-author

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
3 papers
Storage systems · 66% Memory systems · 34%
Software engineering, system software, and programming languages
3 papers
Operating systems · 100%
Network and information security
2 papers
Systems and software security · 89% Network security · 11%
Computer networks
1 paper
Internet architecture and protocols · 100%

Topics — the 9 heaviest of 13, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
flash and SSD
0.612022
Optimizing Storage Performance with Calibrated Interrupts · ACM Trans. Storage 2022
Storage systems › flash and SSD
NVMe storage
0.612022
Optimizing Storage Performance with Calibrated Interrupts · ACM Trans. Storage 2022
Storage systems › i/o architecture › i/o subsystem
storage i/o
0.612022
Optimizing Storage Performance with Calibrated Interrupts · ACM Trans. Storage 2022
Operating systems › kernel
interrupt handling
0.512021
Optimizing Storage Performance with Calibrated Interrupts · OSDI 2021
Memory systems
direct memory access
0.412020
IOctopus: Outsmarting Nonuniform DMA · ASPLOS 2020
Memory systems
non-uniform memory access
0.412020
IOctopus: Outsmarting Nonuniform DMA · ASPLOS 2020
Internet architecture and protocols › network architecture design › layered architecture › protocol layering › network stack
network stack optimization
0.312018
DAMN: Overhead-Free IOMMU Protection for Networking · ASPLOS 2018
Systems and software security
virtualization security
0.212015
Securing Self-Virtualizing Ethernet Devices · USENIX Security Symposium 2015
Operating systems › i/o › i/o subsystem
i/o scheduling
0.212022
Optimizing Storage Performance with Calibrated Interrupts · ACM Trans. Storage 2022

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

calibrated interrupts · 1.1DMA-aware memory allocation · 1.0
YearPublicationVenuePosition
2022 Optimizing Storage Performance with Calibrated Interrupts
abstract
After request completion, an I/O device must decide whether to minimize latency by immediately firing an interrupt or to optimize for throughput by delaying the interrupt, anticipating that more requests will complete soon and help amortize the interrupt cost. Devices employ adaptive interrupt coalescing heuristics that try to balance between these opposing goals. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results. Instead, we propose addressing the root cause of the heuristics problem by allowing software to explicitly specify to the device if submitted requests are latency-sensitive. The device then “calibrates” its interrupts to completions of latency-sensitive requests. We focus on NVMe storage devices and show that it is natural to express these semantics in the kernel and the application and only requires a modest two-bit change to the device interface. Calibrated interrupts increase throughput by up to 35%, reduce CPU consumption by as much as 30%, and achieve up to 37% lower latency when interrupts are coalesced.
Amy Tai, Igor Smolyar, Michael Wei, Dan Tsafrir
ACM Trans. Storage2
2021 Optimizing Storage Performance with Calibrated Interrupts
Amy Tai, Igor Smolyar, Michael Wei, Dan Tsafrir
OSDI2
2020 IOctopus: Outsmarting Nonuniform DMA
abstract
In a multi-CPU server, memory modules are local to the CPU to which they are connected, forming a nonuniform memory access (NUMA) architecture. Because non-local accesses are slower than local accesses, the NUMA architecture might degrade application performance. Similar slowdowns occur when an I/O device issues nonuniform DMA (NUDMA) operations, as the device is connected to memory via a single CPU. NUDMA effects therefore degrade application performance similarly to NUMA effects.
Igor Smolyar, Alex Markuze, Boris Pismenny, Haggai Eran, Gerd Zellweger, Austin Bolen, Liran Liss, Adam Morrison 0001, Dan Tsafrir
ASPLOS1
2018 DAMN: Overhead-Free IOMMU Protection for Networking
abstract
DMA operations can access memory buffers only if they are "mapped" in the IOMMU, so operating systems protect themselves against malicious/errant network DMAs by mapping and unmapping each packet immediately before/after it is DMAed. This approach was recently found to be riskier and less performant than keeping packets non-DMAable and instead copying their content to/from permanently-mapped buffers. Still, the extra copy hampers performance of multi-gigabit networking. We observe that achieving protection at the DMA (un)map boundary is needlessly constraining, as devices must be prevented from changing the data only after the kernel reads it. So there is no real need to switch ownership of buffers between kernel and device at the DMA (un)mapping layer, as opposed to the approach taken by all existing IOMMU protection schemes. We thus eliminate the extra copy by (1)~implementing a new allocator called DMA-Aware Malloc for Networking (DAMN), which (de)allocates packet buffers from a memory pool permanently mapped in the IOMMU; (2)~modifying the network stack to use this allocator; and (3)~copying packet data only when the kernel needs it, which usually morphs the aforementioned extra copy into the kernel's standard copy operation performed at the user-kernel boundary. DAMN thus provides full IOMMU protection with performance comparable to that of an unprotected system.
Alex Markuze, Igor Smolyar, Adam Morrison 0001, Dan Tsafrir
ASPLOS2
2015 Securing Self-Virtualizing Ethernet Devices
Igor Smolyar, Muli Ben-Yehuda, Dan Tsafrir
USENIX Security Symposium1