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14.10.2019
Scale Python GPU code to distributed systems and your laptop.
... computational power if the graph needs it at some point.
Machines like laptops use a "single machine scheduler" that provides basic features on a local process or thread pool. It is simple and cheap to use ...
Scale Python GPU code to distributed systems and your laptop.
18%
19.09.2019
Nvidia GTC 2017 (Listing 1) that is a version of the addition function shown in the previous section. In this version, you control the looping with CUDA variables provided by Numba when you use the
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17.09.2019
of voltage to the conductor, thereby allowing them to shake its atoms in a controllable fashion. As the atoms were made to shake more strongly, they provided a greater source of resistance to the quantum waves
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22.08.2019
from the command (not shown) provides some good information about what it's doing and is useful in understanding what f2py
does.
F2py creates a shared object (.so
) suitable for Python to import:
$ ls
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21.08.2019
platform, which was developed through Cray’s work on exascale systems for the US government, integrates HPC batch workflow scheduling with containerized services, supporting multitenancy and providing a rich ...
New software platform will provide support for exascale computing.
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16.07.2019
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
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collapse(N)
, where N
is the number of loops
in a nested loop that should be collapsed into one “iteration space.” The iteration space is then divided with the schedule
clause, if provided.
A simple
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12.06.2019
New version of the company’s flagship modeling and development platform provides faster simulation and more efficient workflows.
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be exploited to provide additional control and possibly additional performance.
Data and Control Parallelism
A quick review of the do
/for
OpenMP directive brings up some points that should be clarified
18%
03.04.2019
) 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
