Understanding the CPU -intensive and I/O -intensive tasks is essential for optimizing applications and choosing the correct technology stack. These concepts are mainly related to application performance bottlenecks, which can help developers design highly efficient multi -threaded and asynchronous programs.

System model

The computer system can be abstracted as:

<code>輸入 (鍵盤) -> 處理 (CPU) -> 輸出 (顯示器)</code>

Input and output belong to the I/O category, and the calculation is processed by the CPU.

Single program composed of multiple methods or functions in order or parallel execution can be abstracted as:

<code>輸入?yún)?shù) -> 計算 -> 返回值</code>

A distributed service composed of a single -machine service (cluster) running in order or parallel, can be abstracted as:

<code>網(wǎng)絡(luò)請求 (輸入?yún)?shù)) -> 計算 -> 網(wǎng)絡(luò)響應(yīng) (返回值)</code>

The request and response belong to the I/O category, and the calculation is processed by the CPU.

From the perspective of hardware and software, the system consists of I/O operation and CPU calculation.

CPU dense task

CPU -intensive task is mainly limited by the processing speed of the central processor (CPU). These tasks require a lot of calculations, and most of the time are using the CPU instead of waiting for external resources, such as disk I/O or network communication.

The characteristics of the CPU dense task

High computing requirements
• : These tasks usually involve complex mathematical operations, such as video coding/decoding, image processing and scientific computing. Multi -threaded advantages
: On multi -core CPUs, parallel processing can significantly improve the execution efficiency of the CPU -intensive task by allocating workloads to multiple cores.
• High resource consumption :: CPU -intensive tasks often push the CPU utilization rate to nearly 100%during the execution period.
• Common examples

data analysis and large numerical calculations.

graphic rendering or video processing software.

• Cryptocurrency mining.
If your laptop fan is running very loudly, it may be dealing with the CPU -intensive task.
Optimization strategy of CPU dense task

Passralized

: Use multi -core processors to improve performance through parallel computing.

Algorithm optimization
• : Optimize algorithm to reduce unnecessary calculations. Compiler optimization
: Use compilers with high -performance optimization technology.
• I/O -dense task
• I/O -dense tasks are mainly limited by the input/output (I/O) operation, including disk I/O and network communication. The bottleneck of these tasks is to wait for the I/O operation to complete, not computing power.

  I/O -intensive task characteristics

  • High I/O requirements : These tasks frequently read and write files or process a large number of network requests.
  The advantages of concurrent
  • : I/O -intensive tasks benefit from event drive and asynchronous programming models, such as Node.js non -blocking I/O. Low CPU utilization
  : Because most of the time is spent on waiting for external operations, the CPU utilization rate is usually low.
  • Common examples

  handle a large number of web servers and database servers.

  Frequently read and write a disk file server.
  Client applications, such as email clients and social media applications, these applications require frequent network requests and data retrieval.
  • Optimization of I/O -intensive tasks

  Caches

  : Use memory cache to reduce the demand for disk I/O.
  • asynchronous programming : Implement asynchronous I/O operations to avoid obstruction, thereby improving the response speed and throughput.
  Optimization of resource management
  • : Effectively dispatching I/O operations to minimize unnecessary reading and writing.
  node.js and non -blocking I/O
  • Node.js is a well -known implementation of the I/O model. It allows a single thread to process a large number of concurrent client requests through its event -driven architecture.
  What is the non -blocking I/O?

  Non -blocking I/O refers to the input/output operation that will not be forced to complete. This method allows the program to perform other tasks when waiting for the I/O operation.

  Node.js How to deal with non -blocking I/O?

  Node.js runs JavaScript on the V8 engine, and uses the libuv library to achieve non -blocking I/O and asynchronous programming. The key components of non -blocking I/O in Node.js are:

  Incident cycle

  : Node.js Enables the core mechanism of non -blocking I/O. It allows simultaneous processing of network communication, file I/O, user interface operation and timer event.

  Call the stack

  : All synchronous operations (such as the obstruction operation of calculation or direct data processing) is executed in the stack. The lengthy operation in the stack may block the program, causing the "main thread to stagnate."
  • The callback queue : When the asynchronous operation is completed, their callback function will be put into the queue and wait for execution. The event cycle continues to check the queue and move the executable callback to the call stack to execute.
  Non -blocking operation
  • : For the file system operation, Node.js uses the libuv library to use the underlying POSIX non -blocking API to enable the non -blocking function. For network requests, Node.js realizes non -blocking network I/O.
  Consider the following example:
  • In this example, FS.Readfile is asynchronous. Node.js continues to execute Console.log ('Next Step') without waiting for the file to read. After the file is read, the callback function will be queued and finally executed, displaying the content of the file.

  By using the incident -driven callback, a single thread can effectively handle multiple operations, which can significantly improve performance and resource utilization when dealing with I/O -intensive tasks.

  Node.js The non -blocking file system operation

  When node.js performs file system operation (such as reading files), it uses libuv instead of calling the POSIX file system API directly. LIBUV determines the most effective way to perform these operations, while preventing the cycle of the incident from being blocked.

  Libuv maintains a fixed -size thread pool (default: four threads) to perform the blocking I/O operation of the operating system level asynchronously. Therefore, the file I/O operation is performed on these background threads, rather than blocking the loop of the main incident.

  libuv follows Producer-Consumer model , of which:

  • The main thread submits the task (such as file reading request) to the task queue.
  • The thread pool retrieves and executes the task from the queue.
  • After the completion, the work thread notify the main thread to perform the callback function.

  This ensures that the main thread can maintain lightweight and response rapidly even during the heavy I/O operation period.

  

  Conclusion

  Choosing the right processing method and technology stack is essential for improving application performance. For example, Node.js is very suitable for processing I/O -dense Web applications because it has non -blocking I/O models that can effectively manage a large number of concurrent network requests without excessive consumption of thread resources. On the contrary, for the CPU -intensive task, the use of multi -threaded language and platforms (such as Java, C, or GO) can use multi -core CPU processing capabilities.

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