SIMD Numerical Compression Using Bit Packing and Exponent Tokens
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Solution Overview
Problem
High-performance computing systems face bottlenecks due to limited data transfer rates between processor cores and memory, necessitating efficient compression methods for numerical data to reduce storage and transfer demands, while maintaining computational efficiency.
Innovation Solution
The implementation of novel SIMD constructs and instructions for encoding and decoding numerical data, utilizing techniques such as determining maximum exponents, interleaving bits, and generating exponent tokens to compress and decompress data efficiently, leveraging SIMD registers and operations to minimize computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If compression of numerical data is implemented to reduce storage and transfer demands, then data transfer efficiency and memory utilization are improved, but computational overhead increases
Solution Approach 1:
The patent segments numerical data into fixed-point representations, separating integer and fractional parts. This segmentation enables independent processing of each part using optimized SIMD instructions, reducing the computational complexity of compression operations while maintaining data integrity and transfer efficiency.
Solution Approach 2:
The patent replaces traditional sequential compression algorithms with SIMD (Single Instruction Multiple Data) parallel processing mechanisms. This substitution enables simultaneous processing of multiple data elements, dramatically reducing computational overhead and energy consumption while improving data transfer efficiency.
2Speed
If SIMD instructions are used to accelerate compression and decompression operations, then processing speed is improved, but device complexity increases
Solution Approach 1:
The patent develops universal SIMD instruction sequences that can process multiple fixed-point numerical formats (different precision levels) using the same core algorithms. This multi-functionality approach accelerates processing speed across various data types while minimizing the increase in device complexity by reusing the same instruction set.
Solution Approach 2:
The patent utilizes parameter changes in SIMD instructions to adapt to different fixed-point precision requirements. By modifying operational parameters rather than creating separate instruction sets for each precision level, the patent achieves high processing speed while keeping the instruction set complexity manageable.
Data Source
AI summary
Compression and decompression of numerical data utilizing single instruction, multiple data (SIMD) instructions is described. The numerical data includes integer and floating-point samples. Compression supports three encoding modes: lossless, fixed-rate, and fixed-quality. SIMD instructions for compression operations may include attenuation, derivative calculations, bit packing to form compressed packets, header generation for the packets, and packed array output operations. SIMD instructions for decompression may include packed array input operations, header recovery, decoder control, bit unpacking, integration, and amplification. Compression and decompression may be implemented in a microprocessor, digital signal processor, field-programmable gate array, application-specific integrated circuit, system-on-chip, or graphics processor, using SIMD instructions. Compression and decompression of numerical data can reduce memory, networking, and storage bottlenecks. This abstract does not limit the scope of the invention as described in the claims.