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2017-11-26 12:15
2024-9-9 15:21
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1.35 GB
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磁力链接
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Python
Parallel
Programming
Solutions
文件列表
01 - The parallel computing memory architecture - Python Parallel Programming Solutions.mp4
53.42MB
02 - Memory organization - Python Parallel Programming Solutions.mp4
40.22MB
03 - Memory organization continued - Python Parallel Programming Solutions.mp4
31.65MB
04 - Parallel programming models - Python Parallel Programming Solutions.mp4
24.26MB
05 - Designing a parallel program - Python Parallel Programming Solutions.mp4
36.36MB
06 - Evaluating the performance of a parallel program - Python Parallel Programming Solutions.mp4
30.67MB
07 - Introducing Python - Python Parallel Programming Solutions.mp4
35.93MB
08 - Working with processes in Python - Python Parallel Programming Solutions.mp4
13.92MB
09 - Working with threads in Python - Python Parallel Programming Solutions.mp4
20.64MB
10 - Defining a thread - Python Parallel Programming Solutions.mp4
19.58MB
11 - Determining the current thread - Python Parallel Programming Solutions.mp4
6.35MB
12 - Using a thread in a subclass - Python Parallel Programming Solutions.mp4
11.24MB
13 - Thread synchronization with lock - Python Parallel Programming Solutions.mp4
31.04MB
14 - Thread synchronization with RLock - Python Parallel Programming Solutions.mp4
10.04MB
15 - Thread synchronization with semaphores - Python Parallel Programming Solutions.mp4
27.94MB
16 - Thread synchronization with a condition - Python Parallel Programming Solutions.mp4
13.76MB
17 - Thread synchronization with an event - Python Parallel Programming Solutions.mp4
10.43MB
18 - Using the with statement - Python Parallel Programming Solutions.mp4
11.56MB
19 - Thread communication using a queue - Python Parallel Programming Solutions.mp4
17.89MB
20 - Evaluating the performance of multithread applications - Python Parallel Programming Solutions.mp4
26.5MB
21 - Spawning a process - Python Parallel Programming Solutions.mp4
16.07MB
22 - Naming a process - Python Parallel Programming Solutions.mp4
7.09MB
23 - Running a process in the background - Python Parallel Programming Solutions.mp4
7.3MB
24 - Killing a process - Python Parallel Programming Solutions.mp4
8.3MB
25 - Using a process in a subclass - Python Parallel Programming Solutions.mp4
7.77MB
26 - Exchanging objects between processes - Python Parallel Programming Solutions.mp4
16.92MB
27 - Synchronizing processes - Python Parallel Programming Solutions.mp4
15.48MB
28 - Managing a state between processes - Python Parallel Programming Solutions.mp4
8.38MB
29 - Using a process pool - Python Parallel Programming Solutions.mp4
13.57MB
30 - Using the mpi4py Python module - Python Parallel Programming Solutions.mp4
23.08MB
31 - Point-to-point communication - Python Parallel Programming Solutions.mp4
17.23MB
32 - Avoiding deadlock problems - Python Parallel Programming Solutions.mp4
17.86MB
33 - Using broadcast for collective communication - Python Parallel Programming Solutions.mp4
18.29MB
34 - Using scatter for collective communication - Python Parallel Programming Solutions.mp4
12.29MB
35 - Using gather for collective communication - Python Parallel Programming Solutions.mp4
9.51MB
36 - Using alltoall for collective communication - Python Parallel Programming Solutions.mp4
17.77MB
37 - The reduction operation - Python Parallel Programming Solutions.mp4
16.64MB
38 - Optimizing the communication - Python Parallel Programming Solutions.mp4
19.95MB
39 - Using the concurrent.futures Python modules - Python Parallel Programming Solutions.mp4
30.74MB
40 - Event loop management with Asyncio - Python Parallel Programming Solutions.mp4
24.97MB
41 - Handling co-routines with Asyncio - Python Parallel Programming Solutions.mp4
23.54MB
42 - Manipulating a task with Asyncio - Python Parallel Programming Solutions.mp4
13.68MB
43 - Dealing with Asyncio and futures - Python Parallel Programming Solutions.mp4
17.69MB
44 - Using Celery to distribute tasks - Python Parallel Programming Solutions.mp4
19.86MB
45 - Creating a task with Celery - Python Parallel Programming Solutions.mp4
18.11MB
46 - Scientific computing with SCOOP - Python Parallel Programming Solutions.mp4
28.22MB
47 - Handling map functions with SCOOP - Python Parallel Programming Solutions.mp4
23.22MB
48 - Remote method invocation with Pyro4 - Python Parallel Programming Solutions.mp4
29.15MB
49 - Chaining objects with pyro4 - Python Parallel Programming Solutions.mp4
23.1MB
50 - Developing a client-server application with Pyro4 - Python Parallel Programming Solutions.mp4
21.29MB
51 - Communicating sequential processes with PyCSP - Python Parallel Programming Solutions.mp4
39.68MB
52 - A remote procedure call with RPyC - Python Parallel Programming Solutions.mp4
21.06MB
53 - Using the PyCUDA module - Python Parallel Programming Solutions.mp4
43.46MB
54 - Building a PyCUDA application - Python Parallel Programming Solutions.mp4
43.43MB
55 - Understanding the PyCUDA memory model with matrix manipulation - Python Parallel Programming Solutions.mp4
31.39MB
56 - Kernel invocations with GPU array - Python Parallel Programming Solutions.mp4
13.73MB
57 - Evaluating element-wise expressions with PyCUDA - Python Parallel Programming Solutions.mp4
19.2MB
58 - The mapreduce operation with PyCUDA - Python Parallel Programming Solutions.mp4
20.32MB
59 - Gpu programming with NumbaPro - Python Parallel Programming Solutions.mp4
27.51MB
60 - Using GPU-accelerated libraries with NumbaPro - Python Parallel Programming Solutions.mp4
29.87MB
61 - Using the PyOpenCL module - Python Parallel Programming Solutions.mp4
23.42MB
62 - Building a PyOpenCL application - Python Parallel Programming Solutions.mp4
28.6MB
63 - Evaluating element-wise expressions with PyOpenCL - Python Parallel Programming Solutions.mp4
18.24MB
64 - Testing your gpu application with PyOpenCL - Python Parallel Programming Solutions.mp4
24.32MB
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