Quantum Key Distribution Privacy Amplification With Blockwise Memory Access
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional quantum key distribution techniques face challenges in reducing the amount of data transferred to and from external memory during privacy amplification processing, leading to decreased processing performance due to insufficient data transfer bandwidth.
Innovation Solution
Implement a quantum key distribution apparatus with a processor that performs transform processing on input and random number data into a frequency space, storing transformed data in external memory and performing element-wise multiplication and inverse transform operations without accessing external memory, thereby reducing data transfer between local and external memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored in external memory during privacy amplification processing, then data capacity is increased, but data transfer bandwidth becomes insufficient leading to decreased processing performance
Solution Approach 1:
The patent segments the large dataset into multiple blocks that can be processed sequentially. Instead of loading all data into external memory simultaneously, the processor divides the input vector and random number vector into smaller segments, processes them in blocks, and writes results incrementally to external memory. This reduces the peak data transfer bandwidth requirement while maintaining the ability to handle large datasets.
Solution Approach 2:
The patent performs preliminary actions by pre-computing and storing the Hadamard matrix in external memory before the main processing begins. This allows the matrix data to be readily available during the multiplication operations without requiring repeated transfers from internal memory, thereby reducing overall data transfer bandwidth requirements during the critical processing phases.
2Ease of operation
If data is frequently transferred between local and external memory, then data access flexibility is improved, but data transfer time increases
Solution Approach 1:
The patent extracts the most frequently accessed data (input vectors and random number vectors) and keeps them in external memory where they can be efficiently accessed during processing. By organizing the data layout and access patterns, the system minimizes the frequency and volume of data transfers between local and external memory, thereby reducing data transfer time while maintaining operational flexibility.
Solution Approach 2:
The patent implements periodic action by processing data in regular blocks or chunks rather than continuously transferring all data back and forth. The processor periodically loads a block of data from external memory, processes it completely, and writes results back, creating a rhythmic pattern of transfers that optimizes bandwidth utilization and reduces total transfer time compared to frequent small transfers.
Data Source
AI summary
A quantum key distribution apparatus includes a processor implemented by at least one processing device. The processor generates input-vector-transformed data and random-number-transformed data by performing transform processing of transforming an input vector based on a photon received through a quantum channel and random number data based on a hash function into data in a frequency space. The processor stores the input-vector-transformed data and the random-number-transformed data in an external memory. The processor reads a portion of the input-vector-transformed data and a portion of the random-number-transformed data from the external memory into a local memory. The processor performs an element-wise-multiplication-operation of the portion of the input-vector-transformed data and the portion of the random-number-transformed data and inverse-transform processing of an operation result of the element-wise-multiplication-operation without accessing the external memory, and writes an intermediate result of the inverse-transform-processing to the external memory.