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种子名称： [FreeCoursesOnline.Us] Linkedin - Python Parallel Programming Solutions
文件类型： 视频
文件数目： 64个文件
文件大小： 1.35 GB
收录时间： 2017-11-26 12:15
已经下载： 3次
资源热度： 312
最近下载： 2024-12-23 21:26

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[FreeCoursesOnline.Us] Linkedin - Python Parallel Programming Solutions.torrent

01 - The parallel computing memory architecture - Python Parallel Programming Solutions.mp453.42MB

02 - Memory organization - Python Parallel Programming Solutions.mp440.22MB

03 - Memory organization continued - Python Parallel Programming Solutions.mp431.65MB

04 - Parallel programming models - Python Parallel Programming Solutions.mp424.26MB

05 - Designing a parallel program - Python Parallel Programming Solutions.mp436.36MB

06 - Evaluating the performance of a parallel program - Python Parallel Programming Solutions.mp430.67MB

07 - Introducing Python - Python Parallel Programming Solutions.mp435.93MB

08 - Working with processes in Python - Python Parallel Programming Solutions.mp413.92MB

09 - Working with threads in Python - Python Parallel Programming Solutions.mp420.64MB

10 - Defining a thread - Python Parallel Programming Solutions.mp419.58MB

11 - Determining the current thread - Python Parallel Programming Solutions.mp46.35MB

12 - Using a thread in a subclass - Python Parallel Programming Solutions.mp411.24MB

13 - Thread synchronization with lock - Python Parallel Programming Solutions.mp431.04MB

14 - Thread synchronization with RLock - Python Parallel Programming Solutions.mp410.04MB

15 - Thread synchronization with semaphores - Python Parallel Programming Solutions.mp427.94MB

16 - Thread synchronization with a condition - Python Parallel Programming Solutions.mp413.76MB

17 - Thread synchronization with an event - Python Parallel Programming Solutions.mp410.43MB

18 - Using the with statement - Python Parallel Programming Solutions.mp411.56MB

19 - Thread communication using a queue - Python Parallel Programming Solutions.mp417.89MB

20 - Evaluating the performance of multithread applications - Python Parallel Programming Solutions.mp426.5MB

21 - Spawning a process - Python Parallel Programming Solutions.mp416.07MB

22 - Naming a process - Python Parallel Programming Solutions.mp47.09MB

23 - Running a process in the background - Python Parallel Programming Solutions.mp47.3MB

24 - Killing a process - Python Parallel Programming Solutions.mp48.3MB

25 - Using a process in a subclass - Python Parallel Programming Solutions.mp47.77MB

26 - Exchanging objects between processes - Python Parallel Programming Solutions.mp416.92MB

27 - Synchronizing processes - Python Parallel Programming Solutions.mp415.48MB

28 - Managing a state between processes - Python Parallel Programming Solutions.mp48.38MB

29 - Using a process pool - Python Parallel Programming Solutions.mp413.57MB

30 - Using the mpi4py Python module - Python Parallel Programming Solutions.mp423.08MB

31 - Point-to-point communication - Python Parallel Programming Solutions.mp417.23MB

32 - Avoiding deadlock problems - Python Parallel Programming Solutions.mp417.86MB

33 - Using broadcast for collective communication - Python Parallel Programming Solutions.mp418.29MB

34 - Using scatter for collective communication - Python Parallel Programming Solutions.mp412.29MB

35 - Using gather for collective communication - Python Parallel Programming Solutions.mp49.51MB

36 - Using alltoall for collective communication - Python Parallel Programming Solutions.mp417.77MB

37 - The reduction operation - Python Parallel Programming Solutions.mp416.64MB

38 - Optimizing the communication - Python Parallel Programming Solutions.mp419.95MB

39 - Using the concurrent.futures Python modules - Python Parallel Programming Solutions.mp430.74MB

40 - Event loop management with Asyncio - Python Parallel Programming Solutions.mp424.97MB

41 - Handling co-routines with Asyncio - Python Parallel Programming Solutions.mp423.54MB

42 - Manipulating a task with Asyncio - Python Parallel Programming Solutions.mp413.68MB

43 - Dealing with Asyncio and futures - Python Parallel Programming Solutions.mp417.69MB

44 - Using Celery to distribute tasks - Python Parallel Programming Solutions.mp419.86MB

45 - Creating a task with Celery - Python Parallel Programming Solutions.mp418.11MB

46 - Scientific computing with SCOOP - Python Parallel Programming Solutions.mp428.22MB

47 - Handling map functions with SCOOP - Python Parallel Programming Solutions.mp423.22MB

48 - Remote method invocation with Pyro4 - Python Parallel Programming Solutions.mp429.15MB

49 - Chaining objects with pyro4 - Python Parallel Programming Solutions.mp423.1MB

50 - Developing a client-server application with Pyro4 - Python Parallel Programming Solutions.mp421.29MB

51 - Communicating sequential processes with PyCSP - Python Parallel Programming Solutions.mp439.68MB

52 - A remote procedure call with RPyC - Python Parallel Programming Solutions.mp421.06MB

53 - Using the PyCUDA module - Python Parallel Programming Solutions.mp443.46MB

54 - Building a PyCUDA application - Python Parallel Programming Solutions.mp443.43MB

55 - Understanding the PyCUDA memory model with matrix manipulation - Python Parallel Programming Solutions.mp431.39MB

56 - Kernel invocations with GPU array - Python Parallel Programming Solutions.mp413.73MB

57 - Evaluating element-wise expressions with PyCUDA - Python Parallel Programming Solutions.mp419.2MB

58 - The mapreduce operation with PyCUDA - Python Parallel Programming Solutions.mp420.32MB

59 - Gpu programming with NumbaPro - Python Parallel Programming Solutions.mp427.51MB

60 - Using GPU-accelerated libraries with NumbaPro - Python Parallel Programming Solutions.mp429.87MB

61 - Using the PyOpenCL module - Python Parallel Programming Solutions.mp423.42MB

62 - Building a PyOpenCL application - Python Parallel Programming Solutions.mp428.6MB

63 - Evaluating element-wise expressions with PyOpenCL - Python Parallel Programming Solutions.mp418.24MB

64 - Testing your gpu application with PyOpenCL - Python Parallel Programming Solutions.mp424.32MB