LittleFe: The high performance computing education appliance

Ludin, Mobeen; Weeden, Aaron; Houchins, Jennifer; Thompson, Skylar; Peck, Charles; Babic, Ivan; Muterspaw, Kristin; Sergienko, Elena A.

doi:10.1109/cluster.2013.6702649

Cited by 8 publications

(2 citation statements)

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“…[8] 3.3.1 Assignments. The "little iron" project brings together curriculum and a hardware plan that many schools have implemented to teach students high performance computing [16]. The platform itself is made of bare motherboards and metal rods to act as a mounting platform.…”

Section: Bare Hardware To Computational Visualizationmentioning

confidence: 99%

Teaching HPC Systems Administrators

Younts¹,

Harrell²

2020

JOCSE

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The ability to grow and teach systems professionals relies on having the capacity to let students interact with supercomputers at levels not given to normal users. In this paper we describe the teaching methods and hardware platforms used by Purdue Research Computing to train undergraduates for HPC systems-facing roles. From Raspberry Pi clusters to the LittleFe project, previous work has focused on providing miniature hardware platforms and developing curriculums for teaching. Recently, we have developed and employed a method using virtual machines to reach a wider audiences, created best practices, and removed barriers for approaching coursework. This paper outlines the system we have designed, expands on the benets and drawbacks over hardware systems, and discusses the failures and successes we have had teaching HPC System Administrators.

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Section: Bare Hardware To Computational Visualizationmentioning

confidence: 99%

Teaching HPC Systems Administrators

Younts¹,

Harrell²

2020

JOCSE

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“…For some institutions, it may be that no HPC platform is available whatsoever. In this case, one can resort to building lowcost HPC platforms for teaching purposes [1]- [6], to using virtualization and/or container technology to emulate an HPC platform, e.g., in cloud environments [7]- [10], or to gain access to public HPC testbeds. Although a lot can be achieved pedagogically on such platforms, they are not necessarily representative of production HPC platforms (in terms of capabilities, scale, and/or performance behaviors), which can be problematic for performance-oriented learning objectives.…”

Section: Introductionmentioning

confidence: 99%

SMPI Courseware: Teaching Distributed-Memory Computing with MPI in Simulation

Casanova¹,

Legrand²,

Quinson³

et al. 2018

2018 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)

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It is typical in High Performance Computing (HPC) courses to give students access to HPC platforms so that they can benefit from hands-on learning opportunities. Using such platforms, however, comes with logistical and pedagogical challenges. For instance, a logistical challenge is that access to representative platforms must be granted to students, which can be difficult for some institutions or course modalities; and a pedagogical challenge is that hands-on learning opportunities are constrained by the configurations of these platforms.A way to address these challenges is to instead simulate program executions on arbitrary HPC platform configurations. In this work we focus on simulation in the specific context of distributed-memory computing and MPI programming education. While using simulation in this context has been explored in previous works, our approach offers two crucial advantages. First, students write standard MPI programs and can both debug and analyze the performance of their programs in simulation mode. Second, large-scale executions can be simulated in short amounts of time on a single standard laptop computer. This is possible thanks to SMPI, an MPI simulator provided as part of SimGrid. After detailing the challenges involved when using HPC platforms for HPC education and providing background information about SMPI, we present SMPI Courseware. SMPI Courseware is a set of in-simulation assignments that can be incorporated into HPC courses to provide students with hands-on experience for distributed-memory computing and MPI programming learning objectives. We describe some these assignments, highlighting how simulation with SMPI enhances the student learning experience.

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