Samsung electronics co., ltd. (20240354604). NON-LINEAR MULTI-DIMENSIONAL COST FUNCTION FOR ARTIFICIAL INTELLIGENCE INFERENCE simplified abstract
NON-LINEAR MULTI-DIMENSIONAL COST FUNCTION FOR ARTIFICIAL INTELLIGENCE INFERENCE
Organization Name
Inventor(s)
Yotam Platner of Tel-Aviv (IL)
NON-LINEAR MULTI-DIMENSIONAL COST FUNCTION FOR ARTIFICIAL INTELLIGENCE INFERENCE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240354604 titled 'NON-LINEAR MULTI-DIMENSIONAL COST FUNCTION FOR ARTIFICIAL INTELLIGENCE INFERENCE
The abstract of this patent application describes systems and techniques that enable a compiler to optimize tradeoffs and specific user cost functions, such as complex multi-dimensional and non-linear problems, in polynomial time. These techniques can optimize inference tasks based on specific applications in terms of power consumption, idle time, computation efficiency, and system resources. By leveraging these systems and techniques, hardware designers can balance the tradeoff between runtime, power consumption, and resource usage for efficient processing of specialized tasks.
- Optimization of tradeoffs and user cost functions
- Polynomial time optimization
- Balancing runtime, power consumption, and resource usage
- Efficient processing of specialized tasks
- Compiler optimization for specific applications
Potential Applications: - Hardware design - Compiler optimization - Inference tasks - Power consumption optimization
Problems Solved: - Balancing tradeoffs in specialized task processing - Efficient resource allocation - Optimization of power consumption
Benefits: - Improved efficiency in processing specialized tasks - Reduced power consumption - Enhanced system resource utilization
Commercial Applications: Optimizing hardware design for specific applications can lead to more efficient and cost-effective products in industries such as telecommunications, automotive, and consumer electronics.
Questions about Compiler Optimization for Specific Applications: 1. How does the patent application address the tradeoffs in processing specialized tasks? 2. What are the potential benefits of leveraging these systems and techniques for hardware designers?
Original Abstract Submitted
systems and techniques of the present disclosure enable a compiler to optimize such tradeoffs, and further enable optimization for a specific user cost function (e.g., optimization of a complex multi-dimensional and non-linear problem). moreover, the techniques described herein can optimize in polynomial time. accordingly, inference tasks may be optimized (e.g., based on specific applications) in terms of power consumption, idle time, the efficiency of computation, system resources, etc. for instance, by leveraging the systems and techniques described in the present disclosure, hardware designers can balance the tradeoff between runtime, power consumption, and resource usage, which are critical factors in the efficient processing of specialized tasks.
