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HPC Python Programming (Part 2)
Published on Sep 19, 20161155 Views
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Chapter list
Theano in the diffusion equation00:00
Forking01:17
Forking (linux specific)01:50
Process forking, continued04:51
Forking/executing05:11
Notes about fork()06:08
Using fork in data analysis06:52
Threads in Python07:06
Processes versus threads07:51
Notes about threads08:31
How much faster is it using threads? - 108:49
How much faster is it using threads? - 211:07
Not faster at all, slower!11:19
Multiprocessing - 113:18
Multiprocessing - 213:46
The multiprocessing module, continued14:29
Shared memory with multiprocessing - 116:08
Shared memory with multiprocessing - 218:10
Race conditions18:56
Using shared memory, continued19:15
Using shared memory, arrays - 120:17
Using shared memory, arrays - 220:55
But there’s more!21:12
MPI4PY22:05
Message Passing Interface22:57
Mpi4py features24:18
MPI C/C++ recap25:05
MPI Fortran recap25:58
Mpi4py26:13
Mpi4py + numpy31:03
Example: Area under the curve32:01
Mpi4py+numpy: Upper/lowercase example - 132:51
Mpi4py Speedup? - 137:38
Mpi4py Speedup? - 237:48
Mpi4py Speedup? - 338:08
Mpi4py Speedup? - 438:25
Hands-on41:22
Mpi4py+numpy: Upper/lowercase example - 243:48
Map/Reduce variations45:27
Map/reduce48:15
Common characteristics in map/reduce50:49
IPython’s Parallel Architecture53:13
Starting an IPython cluster55:42
Using the workers in python57:14
Accessing the Clients58:56
Accessing the Clients, continued01:00:56
Interfaces to the Engines01:01:27
Views01:01:44
Parallel Execution01:03:15
Blocking/Nonblocking01:04:17
Examples01:04:32
Examples, continued01:04:57
Direct view01:05:10
Direct view, continued01:05:45
Load Balanced View01:05:51
Data movement to and from engines01:06:04
Scatter/Gather01:08:01
Ipyparallel01:09:35
Spark01:13:35
Why Spark?01:13:48
In the beginning01:14:55
Spark’s approach01:16:29
Spark’s anatomy01:18:16
Spark’s anatomy, continued01:19:29
About Spark and pySpark01:19:54
Setting up a Spark session01:20:19
Setting up a Spark session (cont.)01:21:26
Confirming your cluster01:21:59
Creating RDDs01:23:19
RDD Pipelines01:24:21
Creating RDDs, continued01:24:39
Manipulating RDDs: transformations01:25:18
Manipulating RDDs: actions01:26:37
Manipulating RDDs, continued01:27:16