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    19%
    Multicore Processing in Python
    22.08.2017
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    provides a path for Python functions to utilize all of the available cores. In this article, I take a look at what’s possible by writing Python modules in Fortran that use all of the cores on a node
    19%
    System Logging for Data-Based Answers
    25.01.2018
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    system log or a log that you create. The important thing is to pick an approach and stay with it (i.e., don’t mix solutions). If you want or need more granular data than uptime provides for CPU
    19%
    Shared Storage with NFS and SSHFS
    12.09.2018
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    (have you tried getting a filesystem into the kernel?) and provide lots of flexibility. SSHFS uses FUSE to create a filesystem that can be shared by transmitting the data via SSH. The SSHFS FUSE
    19%
    OpenACC – Parallelizing Loops
    09.01.2019
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    . In this fashion, you’ll make the biggest dent in run time with the fewest directives. A simple profile of the application can provide you with the stack rank of the most time consuming routines. As you add
    19%
    OpenACC – Data Management
    07.02.2019
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    that performs specific data movements and provides hints about data usage. Table 1 shows the data directive as it is used in C and Fortran.   Table 1: The data  Directive Fortran C !$acc data
    19%
    High-Performance Python 1
    16.07.2019
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     foreign function library provides C-compatible data types and lets you call functions in dynamic link libraries (DLLs) or shared libraries from within Python. In essence, it “wraps” these libraries so
    19%
    OpenMP – Parallelizing Loops
    03.04.2019
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    ) could “see” all of the others, were coming online. OpenMP provided a very convenient way to write parallel code that could run on all of the processors in the SMP system or a subset of them. As time went
    19%
    Why Good Applications Don’t Scale
    13.10.2020
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    to decrease with n . Some other attempts have been made to account for non-zero communication time in Amdahl’s Law. One of the best is from Bob Brown at Duke. He provides a good analogy of Amdahl’s Law
    19%
    When I/O Workloads Don’t Perform
    12.05.2021
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    provides a nice little utility called iostat that gathers both sets of data. In the example in Listing 6, iostat is showing an extended set of metrics and the CPU utilization at two-second intervals
    19%
    Performance Health Check
    13.06.2022
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    performance of parallel systems, providing a proxy for computation and data movement in computation fluid dynamics (CFD) applications. NPB has been around for many years and has proven to be very useful

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