17944390. MATRIX FORMATION FOR PERFORMING COMPUTATIONAL OPERATIONS IN MEMORY simplified abstract (Micron Technology, Inc.)
Contents
- 1 MATRIX FORMATION FOR PERFORMING COMPUTATIONAL OPERATIONS IN MEMORY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MATRIX FORMATION FOR PERFORMING COMPUTATIONAL OPERATIONS IN MEMORY - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Original Abstract Submitted
MATRIX FORMATION FOR PERFORMING COMPUTATIONAL OPERATIONS IN MEMORY
Organization Name
Inventor(s)
Paolo Fantini of Vimercate (IT)
Maurizio Rizzi of Cologno Monzese (IT)
MATRIX FORMATION FOR PERFORMING COMPUTATIONAL OPERATIONS IN MEMORY - A simplified explanation of the abstract
This abstract first appeared for US patent application 17944390 titled 'MATRIX FORMATION FOR PERFORMING COMPUTATIONAL OPERATIONS IN MEMORY
Simplified Explanation
The abstract describes an innovation involving matrix formation for computational operations in memory, utilizing sub-threshold voltages and sense circuitry to perform operations on data stored in the memory.
- Memory with multiple levels
- Voltage circuitry applies sub-threshold voltages to memory cells
- Sense circuitry senses states of memory cells
- Processing circuitry uses memory cell states to form a matrix and perform computational operations
Potential Applications
This technology could be applied in:
- High-performance computing
- Artificial intelligence
- Data analytics
Problems Solved
This technology addresses issues such as:
- Improving computational efficiency
- Reducing power consumption
- Enhancing memory processing capabilities
Benefits
The benefits of this technology include:
- Faster computational operations
- Lower energy consumption
- Improved memory performance
Potential Commercial Applications
Optimizing Memory Operations for Enhanced Performance
Unanswered Questions
How does this technology compare to traditional memory processing methods?
This article does not provide a direct comparison between this technology and traditional memory processing methods.
Answer: A comparison between this technology and traditional memory processing methods could provide insights into the specific advantages and limitations of each approach, helping stakeholders make informed decisions about adopting this innovation.
What are the potential scalability challenges of implementing this technology in large-scale memory systems?
This article does not address the potential scalability challenges of implementing this technology in large-scale memory systems.
Answer: Understanding the scalability challenges of this technology in large-scale memory systems is crucial for assessing its feasibility and practicality in real-world applications. Further research and development may be needed to address any scalability issues that arise.
Original Abstract Submitted
Apparatuses, methods, and systems for matrix formation for performing computational operations in memory are included. An embodiment includes a memory having a plurality of levels, wherein each of the plurality of levels includes a plurality of memory cells, voltage circuitry configured to apply sub-threshold voltages to the memory cells of each respective level, a plurality of sense lines, sense circuitry coupled to the plurality of sense lines, wherein the sense circuitry coupled to each respective sense line is configured to sense a state for each of the number of memory cells coupled to that respective sense line responsive to the voltage circuitry applying the sub-threshold voltages to the memory cells of each respective level, and processing circuitry configured to utilize the states for each of the memory cells to form a matrix and perform computational operations on data stored in the memory using the matrix.
