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Philip Patchin

dblp:58/7550 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

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

Systems, architecture and hardware · 2

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 · 90% Parallel and multicore computing · 6% Distributed systems · 4%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › virtualization › virtual machine management
virtual machine cloning
0.222011
SnowFlock: Virtual Machine Cloning as a First-Class Cloud Primitive · ACM Trans. Comput. Syst. 2011
SnowFlock: rapid virtual machine cloning for cloud computing · EuroSys 2009
Cloud and datacenter computing
virtualization
0.112011
SnowFlock: Virtual Machine Cloning as a First-Class Cloud Primitive · ACM Trans. Comput. Syst. 2011
Cloud and datacenter computing
resource provisioning
0.112009
SnowFlock: rapid virtual machine cloning for cloud computing · EuroSys 2009
Parallel and multicore computing › parallel programming models and runtimes
parallel programming frameworks
0.012011
SnowFlock: Virtual Machine Cloning as a First-Class Cloud Primitive · ACM Trans. Comput. Syst. 2011

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

microbenchmarking · 0.1implementation · 0.1copy-on-write cloning · 0.1VM fork · 0.1
YearPublicationVenuePosition
2011 SnowFlock: Virtual Machine Cloning as a First-Class Cloud Primitive
abstract
A basic building block of cloud computing is virtualization. Virtual machines (VMs) encapsulate a user’s computing environment and efficiently isolate it from that of other users. VMs, however, are large entities, and no clear APIs exist yet to provide users with programatic, fine-grained control on short time scales. We present SnowFlock, a paradigm and system for cloud computing that introduces VM cloning as a first-class cloud abstraction. VM cloning exploits the well-understood and effective semantics of UNIX fork. We demonstrate multiple usage models of VM cloning: users can incorporate the primitive in their code, can wrap around existing toolchains via scripting, can encapsulate the API within a parallel programming framework, or can use it to load-balance and self-scale clustered servers. VM cloning needs to be efficient to be usable. It must efficiently transmit VM state in order to avoid cloud I/O bottlenecks. We demonstrate how the semantics of cloning aid us in realizing its efficiency: state is propagated in parallel to multiple VM clones, and is transmitted during runtime, allowing for optimizations that substantially reduce the I/O load. We show detailed microbenchmark results highlighting the efficiency of our optimizations, and macrobenchmark numbers demonstrating the effectiveness of the different usage models of SnowFlock.
H. Andrés Lagar-Cavilla, Joseph Andrew Whitney, Roy Bryant, Philip Patchin, Michael Brudno, Eyal de Lara, Stephen M. Rumble, Mahadev Satyanarayanan, Adin Scannell
ACM Trans. Comput. Syst.4
2009 SnowFlock: rapid virtual machine cloning for cloud computing
abstract
Virtual Machine (VM) fork is a new cloud computing abstraction that instantaneously clones a VM into multiple replicas running on different hosts. All replicas share the same initial state, matching the intuitive semantics of stateful worker creation. VM fork thus enables the straightforward creation and efficient deployment of many tasks demanding swift instantiation of stateful workers in a cloud environment, e.g. excess load handling, opportunistic job placement, or parallel computing. Lack of instantaneous stateful cloning forces users of cloud computing into ad hoc practices to manage application state and cycle provisioning. We present SnowFlock, our implementation of the VM fork abstraction. To evaluate SnowFlock, we focus on the demanding scenario of services requiring on-the-fly creation of hundreds of parallel workers in order to solve computationally-intensive queries in seconds. These services are prominent in fields such as bioinformatics, finance, and rendering. SnowFlock provides sub-second VM cloning, scales to hundreds of workers, consumes few cloud I/O resources, and has negligible runtime overhead.
H. Andrés Lagar-Cavilla, Joseph Andrew Whitney, Adin Scannell, Philip Patchin, Stephen M. Rumble, Eyal de Lara, Michael Brudno, Mahadev Satyanarayanan
EuroSys4