[FreeCoursesOnline.Us] Linkedin - Python Parallel Programming Solutions

磁力链接/BT种子名称

[FreeCoursesOnline.Us] Linkedin - Python Parallel Programming Solutions

磁力链接/BT种子简介

种子哈希：4039dff89d1be07dbc3a6ed847e8f7abc6772433
文件大小： 1.35G
已经下载：762次
下载速度：极快
收录时间：2018-03-14
最近下载：2024-11-18

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文件列表

  • 01 - The parallel computing memory architecture - Python Parallel Programming Solutions.en.srt 11.2 kB
  • 01 - The parallel computing memory architecture - Python Parallel Programming Solutions.mp4 56.0 MB
  • 02 - Memory organization - Python Parallel Programming Solutions.en.srt 13.5 kB
  • 02 - Memory organization - Python Parallel Programming Solutions.mp4 42.2 MB
  • 03 - Memory organization continued - Python Parallel Programming Solutions.en.srt 10.8 kB
  • 03 - Memory organization continued - Python Parallel Programming Solutions.mp4 33.2 MB
  • 04 - Parallel programming models - Python Parallel Programming Solutions.en.srt 8.5 kB
  • 04 - Parallel programming models - Python Parallel Programming Solutions.mp4 25.4 MB
  • 05 - Designing a parallel program - Python Parallel Programming Solutions.en.srt 12.6 kB
  • 05 - Designing a parallel program - Python Parallel Programming Solutions.mp4 38.1 MB
  • 06 - Evaluating the performance of a parallel program - Python Parallel Programming Solutions.en.srt 9.6 kB
  • 06 - Evaluating the performance of a parallel program - Python Parallel Programming Solutions.mp4 32.2 MB
  • 07 - Introducing Python - Python Parallel Programming Solutions.en.srt 9.7 kB
  • 07 - Introducing Python - Python Parallel Programming Solutions.mp4 37.7 MB
  • 08 - Working with processes in Python - Python Parallel Programming Solutions.en.srt 4.5 kB
  • 08 - Working with processes in Python - Python Parallel Programming Solutions.mp4 14.6 MB
  • 09 - Working with threads in Python - Python Parallel Programming Solutions.en.srt 6.7 kB
  • 09 - Working with threads in Python - Python Parallel Programming Solutions.mp4 21.6 MB
  • 10 - Defining a thread - Python Parallel Programming Solutions.en.srt 6.7 kB
  • 10 - Defining a thread - Python Parallel Programming Solutions.mp4 20.5 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 6.7 MB
  • 12 - Using a thread in a subclass - Python Parallel Programming Solutions.en.srt 4.0 kB
  • 12 - Using a thread in a subclass - Python Parallel Programming Solutions.mp4 11.8 MB
  • 13 - Thread synchronization with lock - Python Parallel Programming Solutions.en.srt 10.4 kB
  • 13 - Thread synchronization with lock - Python Parallel Programming Solutions.mp4 32.5 MB
  • 14 - Thread synchronization with RLock - Python Parallel Programming Solutions.en.srt 3.5 kB
  • 14 - Thread synchronization with RLock - Python Parallel Programming Solutions.mp4 10.5 MB
  • 15 - Thread synchronization with semaphores - Python Parallel Programming Solutions.en.srt 9.0 kB
  • 15 - Thread synchronization with semaphores - Python Parallel Programming Solutions.mp4 29.3 MB
  • 16 - Thread synchronization with a condition - Python Parallel Programming Solutions.en.srt 4.7 kB
  • 16 - Thread synchronization with a condition - Python Parallel Programming Solutions.mp4 14.4 MB
  • 17 - Thread synchronization with an event - Python Parallel Programming Solutions.en.srt 3.7 kB
  • 17 - Thread synchronization with an event - Python Parallel Programming Solutions.mp4 10.9 MB
  • 18 - Using the with statement - Python Parallel Programming Solutions.en.srt 4.2 kB
  • 18 - Using the with statement - Python Parallel Programming Solutions.mp4 12.1 MB
  • 19 - Thread communication using a queue - Python Parallel Programming Solutions.en.srt 5.9 kB
  • 19 - Thread communication using a queue - Python Parallel Programming Solutions.mp4 18.8 MB
  • 20 - Evaluating the performance of multithread applications - Python Parallel Programming Solutions.en.srt 9.1 kB
  • 20 - Evaluating the performance of multithread applications - Python Parallel Programming Solutions.mp4 27.8 MB
  • 21 - Spawning a process - Python Parallel Programming Solutions.en.srt 5.2 kB
  • 21 - Spawning a process - Python Parallel Programming Solutions.mp4 16.8 MB
  • 22 - Naming a process - Python Parallel Programming Solutions.en.srt 2.5 kB
  • 22 - Naming a process - Python Parallel Programming Solutions.mp4 7.4 MB
  • 23 - Running a process in the background - Python Parallel Programming Solutions.en.srt 2.6 kB
  • 23 - Running a process in the background - Python Parallel Programming Solutions.mp4 7.7 MB
  • 24 - Killing a process - Python Parallel Programming Solutions.en.srt 2.9 kB
  • 24 - Killing a process - Python Parallel Programming Solutions.mp4 8.7 MB
  • 25 - Using a process in a subclass - Python Parallel Programming Solutions.en.srt 2.6 kB
  • 25 - Using a process in a subclass - Python Parallel Programming Solutions.mp4 8.1 MB
  • 26 - Exchanging objects between processes - Python Parallel Programming Solutions.en.srt 5.8 kB
  • 26 - Exchanging objects between processes - Python Parallel Programming Solutions.mp4 17.7 MB
  • 27 - Synchronizing processes - Python Parallel Programming Solutions.en.srt 5.7 kB
  • 27 - Synchronizing processes - Python Parallel Programming Solutions.mp4 16.2 MB
  • 28 - Managing a state between processes - Python Parallel Programming Solutions.en.srt 2.9 kB
  • 28 - Managing a state between processes - Python Parallel Programming Solutions.mp4 8.8 MB
  • 29 - Using a process pool - Python Parallel Programming Solutions.en.srt 4.7 kB
  • 29 - Using a process pool - Python Parallel Programming Solutions.mp4 14.2 MB
  • 30 - Using the mpi4py Python module - Python Parallel Programming Solutions.en.srt 5.7 kB
  • 30 - Using the mpi4py Python module - Python Parallel Programming Solutions.mp4 24.2 MB
  • 31 - Point-to-point communication - Python Parallel Programming Solutions.en.srt 5.7 kB
  • 31 - Point-to-point communication - Python Parallel Programming Solutions.mp4 18.1 MB
  • 32 - Avoiding deadlock problems - Python Parallel Programming Solutions.en.srt 5.7 kB
  • 32 - Avoiding deadlock problems - Python Parallel Programming Solutions.mp4 18.7 MB
  • 33 - Using broadcast for collective communication - Python Parallel Programming Solutions.en.srt 6.0 kB
  • 33 - Using broadcast for collective communication - Python Parallel Programming Solutions.mp4 19.2 MB
  • 34 - Using scatter for collective communication - Python Parallel Programming Solutions.en.srt 4.1 kB
  • 34 - Using scatter for collective communication - Python Parallel Programming Solutions.mp4 12.9 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 10.0 MB
  • 36 - Using alltoall for collective communication - Python Parallel Programming Solutions.en.srt 5.1 kB
  • 36 - Using alltoall for collective communication - Python Parallel Programming Solutions.mp4 18.6 MB
  • 37 - The reduction operation - Python Parallel Programming Solutions.en.srt 5.0 kB
  • 37 - The reduction operation - Python Parallel Programming Solutions.mp4 17.4 MB
  • 38 - Optimizing the communication - Python Parallel Programming Solutions.en.srt 6.4 kB
  • 38 - Optimizing the communication - Python Parallel Programming Solutions.mp4 20.9 MB
  • 39 - Using the concurrent.futures Python modules - Python Parallel Programming Solutions.en.srt 10.3 kB
  • 39 - Using the concurrent.futures Python modules - Python Parallel Programming Solutions.mp4 32.2 MB
  • 40 - Event loop management with Asyncio - Python Parallel Programming Solutions.en.srt 8.6 kB
  • 40 - Event loop management with Asyncio - Python Parallel Programming Solutions.mp4 26.2 MB
  • 41 - Handling co-routines with Asyncio - Python Parallel Programming Solutions.en.srt 7.6 kB
  • 41 - Handling co-routines with Asyncio - Python Parallel Programming Solutions.mp4 24.7 MB
  • 42 - Manipulating a task with Asyncio - Python Parallel Programming Solutions.en.srt 4.3 kB
  • 42 - Manipulating a task with Asyncio - Python Parallel Programming Solutions.mp4 14.3 MB
  • 43 - Dealing with Asyncio and futures - Python Parallel Programming Solutions.en.srt 5.8 kB
  • 43 - Dealing with Asyncio and futures - Python Parallel Programming Solutions.mp4 18.5 MB
  • 44 - Using Celery to distribute tasks - Python Parallel Programming Solutions.en.srt 5.7 kB
  • 44 - Using Celery to distribute tasks - Python Parallel Programming Solutions.mp4 20.8 MB
  • 45 - Creating a task with Celery - Python Parallel Programming Solutions.en.srt 5.4 kB
  • 45 - Creating a task with Celery - Python Parallel Programming Solutions.mp4 19.0 MB
  • 46 - Scientific computing with SCOOP - Python Parallel Programming Solutions.en.srt 8.0 kB
  • 46 - Scientific computing with SCOOP - Python Parallel Programming Solutions.mp4 29.6 MB
  • 47 - Handling map functions with SCOOP - Python Parallel Programming Solutions.en.srt 6.7 kB
  • 47 - Handling map functions with SCOOP - Python Parallel Programming Solutions.mp4 24.3 MB
  • 48 - Remote method invocation with Pyro4 - Python Parallel Programming Solutions.en.srt 8.6 kB
  • 48 - Remote method invocation with Pyro4 - Python Parallel Programming Solutions.mp4 30.6 MB
  • 49 - Chaining objects with pyro4 - Python Parallel Programming Solutions.en.srt 6.3 kB
  • 49 - Chaining objects with pyro4 - Python Parallel Programming Solutions.mp4 24.2 MB
  • 50 - Developing a client-server application with Pyro4 - Python Parallel Programming Solutions.en.srt 5.4 kB
  • 50 - Developing a client-server application with Pyro4 - Python Parallel Programming Solutions.mp4 22.3 MB
  • 51 - Communicating sequential processes with PyCSP - Python Parallel Programming Solutions.en.srt 10.0 kB
  • 51 - Communicating sequential processes with PyCSP - Python Parallel Programming Solutions.mp4 41.6 MB
  • 52 - A remote procedure call with RPyC - Python Parallel Programming Solutions.en.srt 6.2 kB
  • 52 - A remote procedure call with RPyC - Python Parallel Programming Solutions.mp4 22.1 MB
  • 53 - Using the PyCUDA module - Python Parallel Programming Solutions.en.srt 10.4 kB
  • 53 - Using the PyCUDA module - Python Parallel Programming Solutions.mp4 45.6 MB
  • 54 - Building a PyCUDA application - Python Parallel Programming Solutions.en.srt 12.7 kB
  • 54 - Building a PyCUDA application - Python Parallel Programming Solutions.mp4 45.5 MB
  • 55 - Understanding the PyCUDA memory model with matrix manipulation - Python Parallel Programming Solutions.en.srt 9.7 kB
  • 55 - Understanding the PyCUDA memory model with matrix manipulation - Python Parallel Programming Solutions.mp4 32.9 MB
  • 56 - Kernel invocations with GPU array - Python Parallel Programming Solutions.en.srt 4.1 kB
  • 56 - Kernel invocations with GPU array - Python Parallel Programming Solutions.mp4 14.4 MB
  • 57 - Evaluating element-wise expressions with PyCUDA - Python Parallel Programming Solutions.en.srt 5.5 kB
  • 57 - Evaluating element-wise expressions with PyCUDA - Python Parallel Programming Solutions.mp4 20.1 MB
  • 58 - The mapreduce operation with PyCUDA - Python Parallel Programming Solutions.en.srt 6.3 kB
  • 58 - The mapreduce operation with PyCUDA - Python Parallel Programming Solutions.mp4 21.3 MB
  • 59 - Gpu programming with NumbaPro - Python Parallel Programming Solutions.en.srt 8.0 kB
  • 59 - Gpu programming with NumbaPro - Python Parallel Programming Solutions.mp4 28.9 MB
  • 60 - Using GPU-accelerated libraries with NumbaPro - Python Parallel Programming Solutions.en.srt 7.7 kB
  • 60 - Using GPU-accelerated libraries with NumbaPro - Python Parallel Programming Solutions.mp4 31.3 MB
  • 61 - Using the PyOpenCL module - Python Parallel Programming Solutions.en.srt 6.6 kB
  • 61 - Using the PyOpenCL module - Python Parallel Programming Solutions.mp4 24.6 MB
  • 62 - Building a PyOpenCL application - Python Parallel Programming Solutions.en.srt 8.6 kB
  • 62 - Building a PyOpenCL application - Python Parallel Programming Solutions.mp4 30.0 MB
  • 63 - Evaluating element-wise expressions with PyOpenCL - Python Parallel Programming Solutions.en.srt 4.8 kB
  • 63 - Evaluating element-wise expressions with PyOpenCL - Python Parallel Programming Solutions.mp4 19.1 MB
  • 64 - Testing your gpu application with PyOpenCL - Python Parallel Programming Solutions.en.srt 6.5 kB
  • 64 - Testing your gpu application with PyOpenCL - Python Parallel Programming Solutions.mp4 25.5 MB
  • [FreeCoursesOnline.Us].txt 138 Bytes
  • [FreeCoursesOnline.Us].url 123 Bytes
  • [FreeTutorials.Us].txt 75 Bytes
  • [FreeTutorials.Us].url 119 Bytes

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