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Title: Charliecloud: Unprivileged Containers for User-Defined Software Stacks in HPC

  1. Los Alamos National Laboratory
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Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
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Conference: USENIX LISA 2017 ; 2017-10-29 - 2017-11-03 ; San Francisco, California, United States
Country of Publication:
United States
Computer Science; Linux kernel containers docker hpc namespaces

Citation Formats

Jennings, Michael E. Charliecloud: Unprivileged Containers for User-Defined Software Stacks in HPC. United States: N. p., 2017. Web.
Jennings, Michael E. Charliecloud: Unprivileged Containers for User-Defined Software Stacks in HPC. United States.
Jennings, Michael E. 2017. "Charliecloud: Unprivileged Containers for User-Defined Software Stacks in HPC". United States. doi:.
title = {Charliecloud: Unprivileged Containers for User-Defined Software Stacks in HPC},
author = {Jennings, Michael E.},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2017,
month =

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  • Supercomputing centers are seeing increasing demand for user-defined software stacks (UDSS), instead of or in addition to the stack provided by the center. These UDSS support user needs such as complex dependencies or build requirements, externally required configurations, portability, and consistency. The challenge for centers is to provide these services in a usable manner while minimizing the risks: security, support burden, missing functionality, and performance. We present Charliecloud, which uses the Linux user and mount namespaces to run industry-standard Docker containers with no privileged operations or daemons on center resources. Our simple approach avoids most security risks while maintaining accessmore » to the performance and functionality already on offer, doing so in less than 500 lines of code. Charliecloud promises to bring an industry-standard UDSS user workflow to existing, minimally altered HPC resources.« less
  • The authors describe ROSE, a C++ infrastructure for source-to-source translation, that provides an interface for programmers to easily write their own translators for optimizing user-defined high-level abstractions. Utilizing the semantics of these high-level abstractions, they demonstrate the automatic parallelization of loops that iterate over user-defined containers that have interfaces similar to the lists, vectors and sets in the Standard Template Library (STL). The parallelization is realized in two phases. First, they insert OpenMP directives into a serial program, driven by the recognition of the high-level abstractions, containers, that are thread-safe. Then, they translate the OpenMP directives into library routines thatmore » explicitly create and manage parallelism. By providing an interface for the programmer to classify the semantics of their abstractions, they are able to automatically parallelize operations on containers, such as linked-lists, without resorting to complex loop dependence analysis techniques. The approach is consistent with general goals within telescoping languages.« less
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  • In hourly energy simulations, it is important to properly predict the performance of air conditioning systems over a range of full and part load operating conditions. An important component of these calculations is to properly consider the performance of the cycling air conditioner and how it interacts with the building. This paper presents improved approaches to properly account for the part load performance of residential and light commercial air conditioning systems in DOE-2. First, more accurate correlations are given to predict the degradation of system efficiency at part load conditions. In addition, a user-defined function for RESYS is developed thatmore » provides improved predictions of air conditioner sensible and latent capacity at part load conditions. The user function also provides more accurate predictions of space humidity by adding ''lumped'' moisture capacitance into the calculations. The improved cooling coil model and the addition of moisture capacitance predicts humidity swings that are more representative of the performance observed in real buildings.« less