110 research outputs found
Deploying Jupyter Notebooks at scale on XSEDE resources for Science Gateways and workshops
Jupyter Notebooks have become a mainstream tool for interactive computing in
every field of science. Jupyter Notebooks are suitable as companion
applications for Science Gateways, providing more flexibility and
post-processing capability to the users. Moreover they are often used in
training events and workshops to provide immediate access to a pre-configured
interactive computing environment. The Jupyter team released the JupyterHub web
application to provide a platform where multiple users can login and access a
Jupyter Notebook environment. When the number of users and memory requirements
are low, it is easy to setup JupyterHub on a single server. However, setup
becomes more complicated when we need to serve Jupyter Notebooks at scale to
tens or hundreds of users. In this paper we will present three strategies for
deploying JupyterHub at scale on XSEDE resources. All options share the
deployment of JupyterHub on a Virtual Machine on XSEDE Jetstream. In the first
scenario, JupyterHub connects to a supercomputer and launches a single node job
on behalf of each user and proxies back the Notebook from the computing node
back to the user's browser. In the second scenario, implemented in the context
of a XSEDE consultation for the IRIS consortium for Seismology, we deploy
Docker in Swarm mode to coordinate many XSEDE Jetstream virtual machines to
provide Notebooks with persistent storage and quota. In the last scenario we
install the Kubernetes containers orchestration framework on Jetstream to
provide a fault-tolerant JupyterHub deployment with a distributed filesystem
and capability to scale to thousands of users. In the conclusion section we
provide a link to step-by-step tutorials complete with all the necessary
commands and configuration files to replicate these deployments.Comment: 7 pages, 3 figures, PEARC '18: Practice and Experience in Advanced
Research Computing, July 22--26, 2018, Pittsburgh, PA, US
On the relation between the formation of assimilatory pigments and the rate of photosynthesis in etiolated oat seedlings
Thermal stability and topological protection of skyrmions in nanotracks
Magnetic skyrmions are hailed as a potential technology for data storage and
other data processing devices. However, their stability against thermal
fluctuations is an open question that must be answered before skyrmion-based
devices can be designed. In this work, we study paths in the energy landscape
via which the transition between the skyrmion and the uniform state can occur
in interfacial Dzyaloshinskii-Moriya finite-sized systems. We find three
mechanisms the system can take in the process of skyrmion nucleation or
destruction and identify that the transition facilitated by the boundary has a
significantly lower energy barrier than the other energy paths. This clearly
demonstrates the lack of the skyrmion topological protection in finite-sized
magnetic systems. Overall, the energy barriers of the system under
investigation are too small for storage applications at room temperature, but
research into device materials, geometry and design may be able to address
this
Using Jupyter for reproducible scientific workflows
Funding: This work was financially supported by the OpenDreamKit Horizon 2020 European Research Infrastructure project (676541) and the EPSRC Programme grant on Skyrmionics (EP/N032128/1).Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices. In this work, we report two case studies - one in computational magnetism and another in computational mathematics - where a dedicated software was exposed into the Jupyter environment. This enabled interactive and batch computational exploration of data, simulations, data analysis, and workflow documentation and outcome in Jupyter notebooks. In the first study, Ubermag drives existing computational micromagnetics software through a domain-specific language embedded in Python. In the second study, a dedicated Jupyter kernel interfaces with the GAP system for computational discrete algebra and its dedicated programming language. In light of these case studies, we discuss the benefits of this approach, including progress towards more reproducible and re-usable research results and outputs, notably through the use of infrastructure such as JupyterHub and Binder.PostprintPeer reviewe
mage: Fluid Moves Between Code and Graphical Work in Computational Notebooks
We aim to increase the flexibility at which a data worker can choose the
right tool for the job, regardless of whether the tool is a code library or an
interactive graphical user interface (GUI). To achieve this flexibility, we
extend computational notebooks with a new API mage, which supports tools that
can represent themselves as both code and GUI as needed. We discuss the design
of mage as well as design opportunities in the space of flexible code/GUI tools
for data work. To understand tooling needs, we conduct a study with nine
professional practitioners and elicit their feedback on mage and potential
areas for flexible code/GUI tooling. We then implement six client tools for
mage that illustrate the main themes of our study findings. Finally, we discuss
open challenges in providing flexible code/GUI interactions for data workers
ClaimChain: Improving the Security and Privacy of In-band Key Distribution for Messaging
The social demand for email end-to-end encryption is barely supported by
mainstream service providers. Autocrypt is a new community-driven open
specification for e-mail encryption that attempts to respond to this demand. In
Autocrypt the encryption keys are attached directly to messages, and thus the
encryption can be implemented by email clients without any collaboration of the
providers. The decentralized nature of this in-band key distribution, however,
makes it prone to man-in-the-middle attacks and can leak the social graph of
users. To address this problem we introduce ClaimChain, a cryptographic
construction for privacy-preserving authentication of public keys. Users store
claims about their identities and keys, as well as their beliefs about others,
in ClaimChains. These chains form authenticated decentralized repositories that
enable users to prove the authenticity of both their keys and the keys of their
contacts. ClaimChains are encrypted, and therefore protect the stored
information, such as keys and contact identities, from prying eyes. At the same
time, ClaimChain implements mechanisms to provide strong non-equivocation
properties, discouraging malicious actors from distributing conflicting or
inauthentic claims. We implemented ClaimChain and we show that it offers
reasonable performance, low overhead, and authenticity guarantees.Comment: Appears in 2018 Workshop on Privacy in the Electronic Society
(WPES'18
Bacatá: A Language Parametric Notebook Generator (Tool Demo)
\u3cp\u3eInteractive notebooks allow people to communicate and collaborate through a single rich document that might include live code, multimedia, computed results, and documentation, which is persisted as a whole for reproducibility. Notebooks are currently being used extensively in domains such as data science, data journalism, and machine learning. However, constructing a notebook interface for a new language requires a lot of effort. In this tool paper, we present Bacatá, a language parametric notebook generator for domain-specific languages (DSL) based on the Jupyter framework. Bacatá is designed so that language engineers may reuse existing language components (such as parsers, code generators, interpreters, etc.) as much as possible. Moreover, we explain the design of Bacatá and how DSL notebooks can be generated with minimum effort in the context of the Rascal meta programming system and language workbench.\u3c/p\u3
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