Characterized Memory Devices for Cost-Effective Cryptocurrency Mining
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Solution Overview
Problem
Current memory hard cryptocurrency mining using general compute memories is inefficient and costly, as it relies on high manufacturing tolerances to avoid errors, but error-tolerant techniques can enable faster and more cost-effective solutions by utilizing characterized memories with controlled error rates.
Innovation Solution
The use of characterized memories with selected error rates for memory hard applications, including validation stages to ensure accuracy and efficiency, allows for the use of less expensive or defective memories in cryptocurrency mining, leveraging error-tolerant systems to parallelize memory searches and reduce invalid results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If general compute memories with high manufacturing tolerances are used to avoid errors, then reliability is improved, but cost and efficiency worsen
Solution Approach 1:
The system segments the memory system into characterized memories with controlled error rates and separate error correction mechanisms. This allows using lower-cost memories with higher error rates while maintaining overall system reliability through dedicated correction components.
Solution Approach 2:
The patent employs inexpensive characterized memories that can be replaced more easily than traditional high-reliability memories. These memories are designed to operate at higher error rates, reducing cost, while error correction mechanisms handle the increased error burden.
2Reliability
If general compute memories with high manufacturing tolerances are used to avoid errors, then reliability is improved, but productivity worsens
Solution Approach 1:
The system changes the error rate parameter of the memory system by using characterized memories with controlled, higher error rates. This parameter change enables faster operation and higher productivity while error correction mechanisms maintain acceptable reliability levels.
Solution Approach 2:
The error correction mechanisms dynamically adjust to handle the higher error rates from characterized memories, allowing the system to operate at higher speeds. The system adapts its error correction resources to match the increased error burden, enabling improved productivity.
3Productivity
If characterized memories with controlled error rates are used, then productivity is improved, but reliability worsens
Solution Approach 1:
Error correction mechanisms act as intermediaries between the characterized memories and the mining application. These mechanisms translate the high-error-rate memory outputs into reliable results, allowing the system to use fast characterized memories while maintaining data integrity.
Solution Approach 2:
The system implements feedback through error correction mechanisms that detect and correct errors from characterized memories. This feedback loop ensures that even though the memories have higher error rates, the final results maintain the required reliability for cryptocurrency mining.
4Reliability
If validation stages are added to ensure accuracy, then reliability is improved, but device complexity worsens
Solution Approach 1:
The validation functionality is segmented into separate error correction mechanisms rather than being integrated into the main memory structure. This segmentation allows adding validation stages without significantly increasing overall system complexity, as the correction mechanisms are modular and dedicated.
Data Source
AI summary
Methods and apparatus for using characterized devices such as memories. In one embodiment, characterized memories are associated with a range of performances over a range of operational parameters. The characterized memories can be used in conjunction with a solution density function to optimize memory searching. In one exemplary embodiment, a cryptocurrency miner can utilize characterized memories to generate memory hard proof-of-work (POW). The results may be further validated against general compute memories; such that only valid solutions are broadcasted to the mining community. In one embodiment, the validation mechanism is implemented for a plurality of searching apparatus in parallel to provide a more distributed and efficient approach.