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The Secret of Variable Length Encoding: Why LEB128 is a Game Changer for Digital Compression?
In the modern world of data processing, digital compression and encoding techniques are crucial for efficiency. Among them, LEB128 (Little Endian Base 128), as a variable-length data encoding method, has been widely used in many applications. LEB128 not only efficiently stores arbitrarily large integers, but also optimizes data transmission and storage. This article will explore the encoding format, application cases and impact of LEB128 on digital compression technology.
LEB128 encoding format
The encoding method of LEB128 is similar to the variable length quantity (VLQ) format. The main difference is that LEB128 is a little-endian encoding, while the variable length quantity is a big-endian encoding. There are two versions of LEB128: unsigned LEB128 and signed LEB128, and the decoder needs to know whether the encoded value is unsigned or signed.
"LEB128, whether used for unsigned or signed integers, is represented by converting the number into binary form, then grouping the numbers, and finally outputting them as a group of seven bits."
Unsigned LEB128
When encoding an unsigned integer, the number is first represented as binary. The number zero is then extended to a multiple of seven digits (to ensure that if the number is non-zero, the top seven digits are not all zeros). Next, divide the numbers into groups of seven digits. The lowest 7 bits of each byte will contain this set of data, and the uppermost bit of each byte will be set to 1, except for the last byte.
Signed LEB128
Signed integers are encoded similarly to unsigned integers. Starting from the N-bit two's complement representation, group the numbers into groups. So, how to encode -
6 to LEB128?"For signed integers, we invert their binary representation and add one, then group and encode it in the same way as unsigned integers."
Fast decoding technology
Although decoding of LEB128 is simple, purely scalar implementations on modern hardware tend to be slow, especially when the cost of branch prediction is very high. In order to solve this problem, a series of studies have proposed SIMD technology to accelerate decoding, which is called "VByte" technology. The latest "Masked VByte" method demonstrates speed improvements on commodity Haswell hardware, reaching 650 to 2700 million integers per second. On this basis, another paper introduced "Stream VByte" compression technology, which further increases the speed and can reach a decoding speed of more than 400 million integers per second.
Application cases of LEB128
LEB128 has a wide range of applications. For example, in the Dalvik execution format of the Android project, LEB128 is an important part of the file format. In addition, the DWARF file format and LLVM's coverage mapping format also use LEB128 for digital encoding. Other examples include the Minecraft protocol's packet length measurement, the OSU Game Replay Format, the W3C's Efficient XML Interchange Format, and more.
"LEB128's flexibility and efficiency make it the preferred solution for data compression and transmission in many fields, thus greatly improving efficiency."
Related coding technologies
Although LEB128 excels in the field of data compression, there are many other encoding technologies worth noting. For example, Dlugosz's variable-length integer encoding uses different size segments to process integers; Protocol Buffers uses a similar technique in its unsigned integer encoding.
Future Outlook
As data volumes grow significantly, digital compression and encoding technologies will become increasingly important. The evolution of LEB128 technology not only promotes the improvement of data storage and transmission efficiency, but also affects the development of many other encoding technologies. Therefore, we can’t help but think about what innovations will emerge in the future data world and change the way we understand and use numbers?
