Ryan Hancock

dblp:214/0567 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2024
0000-0001-6596-3623ORCID · corroborated

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

Software engineering, systems software and programming languages · 3 · 3 since 2021Systems, architecture and hardware · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2024 MemSnap μCheckpoints: A Data Single Level Store for Fearless Persistence
abstract
Single level stores (SLSes) have recently resurfaced as a system for persisting application data. SLSes like EROS, Aurora, and TreeSLS use application checkpointing to replace file-based APIs. These systems checkpoint at a coarse granularity and must be combined with file persistence mechanisms like WALs, undermining the benefits of their SLS design.
Emil Tsalapatis, Ryan Hancock, Rakeeb Hossain, Ali José Mashtizadeh
ASPLOS (3)2
2022 OrcBench: A Representative Serverless Benchmark
abstract
Serverless computing is rapidly growing area of research. No standardized benchmark currently exists for evaluating orchestration level decisions or executing large serverless workloads because of the limited data provided by cloud providers. Current benchmarks focus on other aspects, such as the cost of running general types of functions and their runtimes.We introduce OrcBench, the first orchestration benchmark based on the recently published Microsoft Azure serverless data set. OrcBench categorizes 8622 serverless functions into 17 distinct models, which represent 5.6 million invocations from the original trace.OrcBench also incorporates a time-series analysis to identify function chains within the dataset. OrcBench can use these to create workloads that mimic complete serverless applications, which includes simulating CPU and memory usage. The modeling allows these workloads to be scaled according to the target hardware configuration.
Ryan Hancock, Sreeharsha Udayashankar, Ali José Mashtizadeh, Samer Al-Kiswany
CLOUD1
2021 The Aurora operating system: revisiting the single level store
abstract
Applications on modern operating systems manage their ephemeral state in memory, and persistent state on disk. Ensuring consistency between them is a source of significant developer effort, yet still a source of significant bugs in mature applications. We present the Aurora single level store (SLS), an OS that simplifies persistence by automatically persisting all traditionally ephemeral application state. With recent storage hardware like NVMe SSDs and NVDIMMs, Aurora is able to continuously checkpoint entire applications with millisecond granularity.
Emil Tsalapatis, Ryan Hancock, Tavian Barnes, Ali José Mashtizadeh
HotOS2
2021 The Aurora Single Level Store Operating System
abstract
Applications on modern operating systems manage their ephemeral state in memory and persistent state on disk. Ensuring consistency between them is a source of significant developer effort and application bugs. We present the Aurora single level store, an OS that eliminates the distinction between ephemeral and persistent application state.
Emil Tsalapatis, Ryan Hancock, Tavian Barnes, Ali José Mashtizadeh
SOSP2