Type | devroom |
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2/6/21 |
With the end of Moore’s law, improving single-core processor performance can be extremely difficult to do in an energy-efficient manner. One alternative is to rethink conventional processor design methodologies and propose innovative ideas to unlock additional performance and efficiency. In an attempt to overcome these difficulties, we propose a compiler-informed non-speculative out-of-order commit processor, that attacks the limitations of in-order commit in current out-of-order cores to ...
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2/6/21 |
Over the years, there has been extensive and continuous effort on improving Spark SQL's query optimizer and planner, in order to generate high quality query execution plans. One of the biggest improvements is the cost-based optimization framework that collects and leverages a variety of data statistics (e.g., row count, number of distinct values, NULL values, max/min values, etc.) to help Spark make better decisions in picking the most optimal query plan.
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2/6/21 |
This talk introduces DiscoPoP, a tool which identifies parallelization opportunities in sequential programs and suggests programmers how to parallelize them using OpenMP. The tool first identifies computational units which, in our terminology, are the atoms of parallelization. Then, it profiles memory accesses inside the source code to detect data dependencies. Mapping dependencies to CUs, we create a data structure which we call the program execution tree (PET). Further, DiscoPoP inspects the ...
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2/6/21 |
In this talk we explore two programming models for GPU accelerated computing in a Fortran application: OpenMP with target directives and CUDA. We use an example application Riemann problem, a common problem in fluid dynamics, as our testing ground. This example application is implemented in GenASiS, a code being developed for astrophysics simulations. While OpenMP and CUDA are supported on the Summit supercomputer, its successor, an exascale supercomputer Frontier, will support OpenMP and ...
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2/6/21 |
The European Environment for Scientific Software Installations (EESSI, pronounced as “easy”) is a collaboration between different HPC sites and industry partners, with the common goal to set up a shared repository of scientific software installations that can be used on a variety of systems, regardless of which flavor/version of Linux distribution or processor architecture is used, or whether it is a full-size HPC cluster, a cloud environment or a personal workstation. The EESSI codebase ...
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2/6/21 |
XALT is a tool run on clusters to find out what programs and libraries are run. XALT uses the environment variable LD_PRELOAD to attach a shared library to execute code before and after main(). This means that the XALT shared library is a developer on every program run under linux. This shared library is part of every program run. This talk will discuss the various lessons about routine names and memory usage. Adding XALT to track container usage presents new issues because of what shared ...
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2/6/21 |
In this sessions we are presenting several approaches to migrate from traditional HPC to cloud-native, containerized HPC using an ensemble run of the molecular dynamics code GROMACS as an example. The session will show how containerization via software management is coming to the rescue and how a palatable journey might look like.
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