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Bitmap can greatly compress non-repeating data within a certain range and elegantly represent a set of boolean values, occupying a small space and providing fast query speed.

Application Scenarios#

1. Set Operations

   • Deduplication: Bitmap can be used for fast deduplication. For example, when processing a large amount of data, a bitmap can be used to record whether a certain data has already appeared.

   • Intersection, Union, Difference: Bitmap is very efficient in processing the intersection, union, and difference of sets.

2. Boolean Arrays

   • Boolean Marking: Bitmap can be used to represent a large number of boolean marks. For example, in a compiler, it can record whether a variable is used.

   • Task Status: Bitmap can be used to represent the status of tasks or processes, such as whether a task has been completed.

3. Space Optimization

   • Memory Management: In operating systems, bitmaps are commonly used for memory allocation management, recording which memory blocks have been used.

   • Disk Space Management: Bitmaps are used to record the usage of disk blocks, indicating which blocks are free and which blocks are already in use.

4. Data Filtering

   • Bloom Filter: Bloom filter uses multiple bitmaps to quickly determine whether an element is in a set, with the advantages of efficiency and low memory usage.

5. Parallel Computing

   • Thread Management: Bitmap is used to manage the status of threads, indicating which threads are active and which threads have completed.

6. Image Processing

   • Image Representation: In image processing, bitmaps are used to represent the pixel values of black and white images, with each bit representing whether a pixel is black or white.

Bitmap has a wide range of applications in the Linux system#

1. Memory Management

   • Buddy System: The memory management in the Linux kernel uses the buddy system to allocate and free memory blocks. Bitmaps are used to record the usage of each memory block, enabling fast lookup of free memory blocks.

2. File System
   • ext2/ext3/ext4 File System: These file systems use bitmaps to manage data blocks and inodes on disks. The bitmaps record which data blocks and inodes are used and which are free, enabling efficient disk space management.

3. Process Management
   • CPU Affinity: Bitmaps are used to represent the set of CPUs on which a process can run. By setting and retrieving the CPU affinity of a process using bitmaps, process scheduling and system performance can be optimized.

4. Device Management
   • Device Bitmap: Bitmaps are used to manage the status of devices, such as the status (enabled/disabled) of network devices and the allocation of devices.

5. Virtual Memory
   • Page Frame Allocator: Bitmaps are used to manage the allocation status of physical page frames, tracking which page frames have been allocated and which are free, enabling efficient page frame allocation and reclamation.

Applications of Bitmap in the Front-end Scope#

1. Image Processing - canvas can directly manipulate pixel data.
2. Bitmap Fonts - suitable for low-resolution and retro game design, rendering faster and saving space.
3. Bloom Filter - fast query.
4. Front-end Permission Management - storing user permissions in bitmaps, allowing storage of a large amount of permission information with low occupancy and performance.

Implementation of Bitmap Structure in JavaScript - Based on Uint8Array#

class Bitmap {
  constructor(size) {
    this.size = size;
    this.data = new Uint8Array(Math.ceil(size / 8));
  }

  // Set the index-th bit to 1
  set(index) {
    if (index >= this.size) throw new RangeError('Index out of bounds');
    const byteIndex = Math.floor(index / 8);
    const bitIndex = index % 8;
    this.data[byteIndex] |= (1 << bitIndex);
  }

  // Clear the index-th bit (set to 0)
  clear(index) {
    if (index >= this.size) throw new RangeError('Index out of bounds');
    const byteIndex = Math.floor(index / 8);
    const bitIndex = index % 8;
    this.data[byteIndex] &= ~(1 << bitIndex);
  }

  // Get the value of the index-th bit
  get(index) {
    if (index >= this.size) throw new RangeError('Index out of bounds');
    const byteIndex = Math.floor(index / 8);
    const bitIndex = index % 8;
    return (this.data[byteIndex] & (1 << bitIndex)) !== 0;
  }
}