Adaptive Quantization for Analog In-Memory Computing Systems

The patent applies parameter changes by dynamically adjusting the quantization bit-depth based on the calculated error metrics. When error exceeds the threshold, the system increases quantization precision (changes the parameter of quantization bits), thereby improving calculation accuracy without permanently increasing system complexity. This adaptive parameter adjustment resolves the contradiction by allowing the system to maintain high throughput while compensating for noise sensitivity through selective precision enhancement.

The patent implements a feedback mechanism where the system continuously monitors calculation errors in the analog IMC system and uses this information to adjust quantization parameters. The error calculation unit computes differences between expected and actual results, and this feedback drives the adaptive quantization process. This closed-loop feedback resolves the contradiction by enabling the system to maintain high throughput while automatically compensating for noise-induced accuracy degradation through real-time parameter adjustment.

The patent applies dynamics by making the quantization bit-depth adaptive rather than static. The system dynamically adjusts the number of bits used for quantization based on real-time error measurements and calculated thresholds. This dynamic approach resolves the contradiction by allowing the system to use higher precision only when and where needed, rather than uniformly across all operations, thereby maintaining accuracy while minimizing hardware complexity and resource utilization.

The patent changes the quantization parameter (bit-depth) based on error thresholds and performance requirements. Instead of using fixed high precision throughout the system, the patent adjusts the precision parameter adaptively, increasing it only when error exceeds acceptable levels. This parameter change strategy resolves the contradiction by enabling high accuracy when necessary while avoiding the constant hardware overhead associated with fixed high-precision quantization.

The patent applies self-service by enabling existing hardware to adapt and optimize its own performance through the adaptive quantization mechanism. The system uses the available hardware resources and automatically adjusts quantization parameters to meet performance specifications without requiring additional hardware infrastructure. This self-service approach resolves the contradiction by allowing existing hardware to achieve higher throughput and performance through intelligent parameter adaptation rather than through hardware upgrades.

The patent changes operational parameters (quantization bit-depth, thresholds) of existing hardware to extract maximum performance from the available infrastructure. By dynamically adjusting these parameters based on error metrics and performance requirements, the system enables existing hardware to meet throughput specifications that would otherwise require more powerful or additional hardware. This parameter adaptation resolves the contradiction by achieving high performance through software-controlled parameter optimization rather than hardware expansion.