[FreeCoursesOnline.Us] Linkedin - Python Parallel Programming Solutions

File Name

Size

01 - The parallel computing memory architecture - Python Parallel Programming Solutions.en.srt

11 kB

01 - The parallel computing memory architecture - Python Parallel Programming Solutions.mp4

53 MB

02 - Memory organization - Python Parallel Programming Solutions.en.srt

13 kB

02 - Memory organization - Python Parallel Programming Solutions.mp4

40 MB

03 - Memory organization continued - Python Parallel Programming Solutions.en.srt

10 kB

03 - Memory organization continued - Python Parallel Programming Solutions.mp4

32 MB

04 - Parallel programming models - Python Parallel Programming Solutions.en.srt

8.3 kB

04 - Parallel programming models - Python Parallel Programming Solutions.mp4

24 MB

05 - Designing a parallel program - Python Parallel Programming Solutions.en.srt

12 kB

05 - Designing a parallel program - Python Parallel Programming Solutions.mp4

36 MB

06 - Evaluating the performance of a parallel program - Python Parallel Programming Solutions.en.srt

9.4 kB

06 - Evaluating the performance of a parallel program - Python Parallel Programming Solutions.mp4

31 MB

07 - Introducing Python - Python Parallel Programming Solutions.en.srt

9.5 kB

07 - Introducing Python - Python Parallel Programming Solutions.mp4

36 MB

08 - Working with processes in Python - Python Parallel Programming Solutions.en.srt

4.4 kB

08 - Working with processes in Python - Python Parallel Programming Solutions.mp4

14 MB

09 - Working with threads in Python - Python Parallel Programming Solutions.en.srt

6.6 kB

09 - Working with threads in Python - Python Parallel Programming Solutions.mp4

21 MB

10 - Defining a thread - Python Parallel Programming Solutions.en.srt

6.5 kB

10 - Defining a thread - Python Parallel Programming Solutions.mp4

20 MB

11 - Determining the current thread - Python Parallel Programming Solutions.en.srt

2.3 kB

11 - Determining the current thread - Python Parallel Programming Solutions.mp4

6.3 MB

12 - Using a thread in a subclass - Python Parallel Programming Solutions.en.srt

3.9 kB

12 - Using a thread in a subclass - Python Parallel Programming Solutions.mp4

11 MB

13 - Thread synchronization with lock - Python Parallel Programming Solutions.en.srt

10 kB

13 - Thread synchronization with lock - Python Parallel Programming Solutions.mp4

31 MB

14 - Thread synchronization with RLock - Python Parallel Programming Solutions.en.srt

3.4 kB

14 - Thread synchronization with RLock - Python Parallel Programming Solutions.mp4

10 MB

15 - Thread synchronization with semaphores - Python Parallel Programming Solutions.en.srt

8.7 kB

15 - Thread synchronization with semaphores - Python Parallel Programming Solutions.mp4

28 MB

16 - Thread synchronization with a condition - Python Parallel Programming Solutions.en.srt

4.6 kB

16 - Thread synchronization with a condition - Python Parallel Programming Solutions.mp4

14 MB

17 - Thread synchronization with an event - Python Parallel Programming Solutions.en.srt

3.6 kB

17 - Thread synchronization with an event - Python Parallel Programming Solutions.mp4

10 MB

18 - Using the with statement - Python Parallel Programming Solutions.en.srt

4.1 kB

18 - Using the with statement - Python Parallel Programming Solutions.mp4

12 MB

19 - Thread communication using a queue - Python Parallel Programming Solutions.en.srt

5.8 kB

19 - Thread communication using a queue - Python Parallel Programming Solutions.mp4

18 MB

20 - Evaluating the performance of multithread applications - Python Parallel Programming Solutions.en.srt

8.9 kB

20 - Evaluating the performance of multithread applications - Python Parallel Programming Solutions.mp4

26 MB

21 - Spawning a process - Python Parallel Programming Solutions.en.srt

5.1 kB

21 - Spawning a process - Python Parallel Programming Solutions.mp4

16 MB

22 - Naming a process - Python Parallel Programming Solutions.en.srt

2.4 kB

22 - Naming a process - Python Parallel Programming Solutions.mp4

7.1 MB

23 - Running a process in the background - Python Parallel Programming Solutions.en.srt

2.5 kB

23 - Running a process in the background - Python Parallel Programming Solutions.mp4

7.3 MB

24 - Killing a process - Python Parallel Programming Solutions.en.srt

2.8 kB

24 - Killing a process - Python Parallel Programming Solutions.mp4

8.3 MB

25 - Using a process in a subclass - Python Parallel Programming Solutions.en.srt

2.5 kB

25 - Using a process in a subclass - Python Parallel Programming Solutions.mp4

7.8 MB

26 - Exchanging objects between processes - Python Parallel Programming Solutions.en.srt

5.7 kB

26 - Exchanging objects between processes - Python Parallel Programming Solutions.mp4

17 MB

27 - Synchronizing processes - Python Parallel Programming Solutions.en.srt

5.6 kB

27 - Synchronizing processes - Python Parallel Programming Solutions.mp4

16 MB

28 - Managing a state between processes - Python Parallel Programming Solutions.en.srt

2.8 kB

28 - Managing a state between processes - Python Parallel Programming Solutions.mp4

8.4 MB

29 - Using a process pool - Python Parallel Programming Solutions.en.srt

4.6 kB

29 - Using a process pool - Python Parallel Programming Solutions.mp4

14 MB

30 - Using the mpi4py Python module - Python Parallel Programming Solutions.en.srt

5.6 kB

30 - Using the mpi4py Python module - Python Parallel Programming Solutions.mp4

23 MB

31 - Point-to-point communication - Python Parallel Programming Solutions.en.srt

5.6 kB

31 - Point-to-point communication - Python Parallel Programming Solutions.mp4

17 MB

32 - Avoiding deadlock problems - Python Parallel Programming Solutions.en.srt

5.6 kB

32 - Avoiding deadlock problems - Python Parallel Programming Solutions.mp4

18 MB

33 - Using broadcast for collective communication - Python Parallel Programming Solutions.en.srt

5.9 kB

33 - Using broadcast for collective communication - Python Parallel Programming Solutions.mp4

18 MB

34 - Using scatter for collective communication - Python Parallel Programming Solutions.en.srt

4.0 kB

34 - Using scatter for collective communication - Python Parallel Programming Solutions.mp4

12 MB

35 - Using gather for collective communication - Python Parallel Programming Solutions.en.srt

3.0 kB

35 - Using gather for collective communication - Python Parallel Programming Solutions.mp4

9.5 MB

36 - Using alltoall for collective communication - Python Parallel Programming Solutions.en.srt

5.0 kB

36 - Using alltoall for collective communication - Python Parallel Programming Solutions.mp4

18 MB

37 - The reduction operation - Python Parallel Programming Solutions.en.srt

4.9 kB

37 - The reduction operation - Python Parallel Programming Solutions.mp4

17 MB

38 - Optimizing the communication - Python Parallel Programming Solutions.en.srt

6.2 kB

38 - Optimizing the communication - Python Parallel Programming Solutions.mp4

20 MB

39 - Using the concurrent.futures Python modules - Python Parallel Programming Solutions.en.srt

10 kB

39 - Using the concurrent.futures Python modules - Python Parallel Programming Solutions.mp4

31 MB

40 - Event loop management with Asyncio - Python Parallel Programming Solutions.en.srt

8.4 kB

40 - Event loop management with Asyncio - Python Parallel Programming Solutions.mp4

25 MB

41 - Handling co-routines with Asyncio - Python Parallel Programming Solutions.en.srt

7.4 kB

41 - Handling co-routines with Asyncio - Python Parallel Programming Solutions.mp4

24 MB

42 - Manipulating a task with Asyncio - Python Parallel Programming Solutions.en.srt

4.2 kB

42 - Manipulating a task with Asyncio - Python Parallel Programming Solutions.mp4

14 MB

43 - Dealing with Asyncio and futures - Python Parallel Programming Solutions.en.srt

5.7 kB

43 - Dealing with Asyncio and futures - Python Parallel Programming Solutions.mp4

18 MB

44 - Using Celery to distribute tasks - Python Parallel Programming Solutions.en.srt

5.5 kB

44 - Using Celery to distribute tasks - Python Parallel Programming Solutions.mp4

20 MB

45 - Creating a task with Celery - Python Parallel Programming Solutions.en.srt

5.3 kB

45 - Creating a task with Celery - Python Parallel Programming Solutions.mp4

18 MB

46 - Scientific computing with SCOOP - Python Parallel Programming Solutions.en.srt

7.8 kB

46 - Scientific computing with SCOOP - Python Parallel Programming Solutions.mp4

28 MB

47 - Handling map functions with SCOOP - Python Parallel Programming Solutions.en.srt

6.5 kB

47 - Handling map functions with SCOOP - Python Parallel Programming Solutions.mp4

23 MB

48 - Remote method invocation with Pyro4 - Python Parallel Programming Solutions.en.srt

8.4 kB

48 - Remote method invocation with Pyro4 - Python Parallel Programming Solutions.mp4

29 MB

49 - Chaining objects with pyro4 - Python Parallel Programming Solutions.en.srt

6.1 kB

49 - Chaining objects with pyro4 - Python Parallel Programming Solutions.mp4

23 MB

50 - Developing a client-server application with Pyro4 - Python Parallel Programming Solutions.en.srt

5.3 kB

50 - Developing a client-server application with Pyro4 - Python Parallel Programming Solutions.mp4

21 MB

51 - Communicating sequential processes with PyCSP - Python Parallel Programming Solutions.en.srt

9.8 kB

51 - Communicating sequential processes with PyCSP - Python Parallel Programming Solutions.mp4

40 MB

52 - A remote procedure call with RPyC - Python Parallel Programming Solutions.en.srt

6.0 kB

52 - A remote procedure call with RPyC - Python Parallel Programming Solutions.mp4

21 MB

53 - Using the PyCUDA module - Python Parallel Programming Solutions.en.srt

10 kB

53 - Using the PyCUDA module - Python Parallel Programming Solutions.mp4

44 MB

54 - Building a PyCUDA application - Python Parallel Programming Solutions.en.srt

12 kB

54 - Building a PyCUDA application - Python Parallel Programming Solutions.mp4

43 MB

55 - Understanding the PyCUDA memory model with matrix manipulation - Python Parallel Programming Solutions.en.srt

9.5 kB

55 - Understanding the PyCUDA memory model with matrix manipulation - Python Parallel Programming Solutions.mp4

31 MB

56 - Kernel invocations with GPU array - Python Parallel Programming Solutions.en.srt

4.0 kB

56 - Kernel invocations with GPU array - Python Parallel Programming Solutions.mp4

14 MB

57 - Evaluating element-wise expressions with PyCUDA - Python Parallel Programming Solutions.en.srt

5.3 kB

57 - Evaluating element-wise expressions with PyCUDA - Python Parallel Programming Solutions.mp4

19 MB

58 - The mapreduce operation with PyCUDA - Python Parallel Programming Solutions.en.srt

6.2 kB

58 - The mapreduce operation with PyCUDA - Python Parallel Programming Solutions.mp4

20 MB

59 - Gpu programming with NumbaPro - Python Parallel Programming Solutions.en.srt

7.8 kB

59 - Gpu programming with NumbaPro - Python Parallel Programming Solutions.mp4

28 MB

60 - Using GPU-accelerated libraries with NumbaPro - Python Parallel Programming Solutions.en.srt

7.5 kB

60 - Using GPU-accelerated libraries with NumbaPro - Python Parallel Programming Solutions.mp4

30 MB

61 - Using the PyOpenCL module - Python Parallel Programming Solutions.en.srt

6.4 kB

61 - Using the PyOpenCL module - Python Parallel Programming Solutions.mp4

23 MB

62 - Building a PyOpenCL application - Python Parallel Programming Solutions.en.srt

8.4 kB

62 - Building a PyOpenCL application - Python Parallel Programming Solutions.mp4

29 MB

63 - Evaluating element-wise expressions with PyOpenCL - Python Parallel Programming Solutions.en.srt

4.7 kB

63 - Evaluating element-wise expressions with PyOpenCL - Python Parallel Programming Solutions.mp4

18 MB

64 - Testing your gpu application with PyOpenCL - Python Parallel Programming Solutions.en.srt

6.3 kB

64 - Testing your gpu application with PyOpenCL - Python Parallel Programming Solutions.mp4

24 MB

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123 B

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75 B

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119 B