Tim Stamler

dblp:178/4786 · also Timothy Stamler · DBLP profile ↗
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5ranked-venue papers
1as first author
3since 2021 · last 2022
—ORCID · none

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

Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021Computer networks · 1 · 1 since 2021
YearPublicationVenuePosition
2022 FlexTOE: Flexible TCP Offload with Fine-Grained Parallelism
Rajath Shashidhara, Tim Stamler, Antoine Kaufmann, Simon Peter 0001
NSDI2
2022 zIO: Accelerating IO-Intensive Applications with Transparent Zero-Copy IO
Tim Stamler, Deukyeon Hwang, Amanda Raybuck, Simon Peter 0001
OSDI1
2021 HeMem: Scalable Tiered Memory Management for Big Data Applications and Real NVM
abstract
High-capacity non-volatile memory (NVM) is a new main memory tier. Tiered DRAM+NVM servers increase total memory capacity by up to 8x, but can diminish memory bandwidth by up to 7x and inflate latency by up to 63% if not managed well. We study existing hardware and software tiered memory management systems on the recently available Intel Optane DC NVM with big data applications and find that no existing system maximizes application performance on real NVM.
Amanda Raybuck, Tim Stamler, Mattan Erez, Simon Peter 0001
SOSP2
2019 TAS: TCP Acceleration as an OS Service
abstract
As datacenter network speeds rise, an increasing fraction of server CPU cycles is consumed by TCP packet processing, in particular for remote procedure calls (RPCs). To free server CPUs from this burden, various existing approaches have attempted to mitigate these overheads, by bypassing the OS kernel, customizing the TCP stack for an application, or by offloading packet processing to dedicated hardware. In doing so, these approaches trade security, agility, or generality for efficiency. Neither trade-off is fully desirable in the fast-evolving commodity cloud.
Antoine Kaufmann, Tim Stamler, Simon Peter 0001, Naveen Kr. Sharma, Arvind Krishnamurthy, Thomas E. Anderson
EuroSys2
2016 Parallel sections: scaling system-level data-structures
abstract
As systems continue to increase the number of cores within cache coherency domains, traditional techniques for enabling parallel computation on data-structures are increasingly strained. A single contended cache-line bouncing between different caches can prohibit continued performance gains with additional cores. New abstractions and mechanisms are required to reassess how data-structure consistency can be provided, while maintaining stable per-core access latencies.
Tim Stamler, Gabriel Parmer
EuroSys2