Intel corporation (20240103874). INSTRUCTION ELIMINATION THROUGH HARDWARE DRIVEN MEMOIZATION OF LOOP INSTANCES simplified abstract
Contents
- 1 INSTRUCTION ELIMINATION THROUGH HARDWARE DRIVEN MEMOIZATION OF LOOP INSTANCES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INSTRUCTION ELIMINATION THROUGH HARDWARE DRIVEN MEMOIZATION OF LOOP INSTANCES - 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 Possible Prior Art
- 1.9.1 Unanswered Questions
- 1.9.2 How does this hardware-driven memoization technique compare to software-based memoization techniques in terms of performance and efficiency?
- 1.9.3 What are the potential limitations or drawbacks of implementing this hardware-driven memoization technique in existing systems?
- 1.10 Original Abstract Submitted
INSTRUCTION ELIMINATION THROUGH HARDWARE DRIVEN MEMOIZATION OF LOOP INSTANCES
Organization Name
Inventor(s)
Niranjan Kumar Soundararajan of Bengaluru (IN)
Sreenivas Subramoney of Bangalore (IN)
INSTRUCTION ELIMINATION THROUGH HARDWARE DRIVEN MEMOIZATION OF LOOP INSTANCES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240103874 titled 'INSTRUCTION ELIMINATION THROUGH HARDWARE DRIVEN MEMOIZATION OF LOOP INSTANCES
Simplified Explanation
The patent application describes a hardware-driven memoization technique for eliminating instructions of loop instances by learning repeating sequences of loops and transparently removing instructions for the loop instructions from instruction sequences while providing their output to dependent instructions.
- Hardware-driven memoization technique for instruction elimination
- Path-based predictor at the front-end to predict loop instances
- Memoization prediction micro-operation (uop) inserted into instruction sequences for predicted loop instances
- Input signature based on all live-ins of a loop, including register-based live-ins and memory loads in the loop body
Potential Applications
This technology could be applied in:
- High-performance computing systems
- Embedded systems
- Real-time systems
Problems Solved
- Reducing instruction overhead in loop instances
- Improving performance by eliminating redundant instructions
- Enhancing efficiency of hardware operations
Benefits
- Increased speed and efficiency in loop execution
- Reduced power consumption
- Enhanced overall system performance
Potential Commercial Applications
- Processor manufacturers
- System integrators
- Software developers
Possible Prior Art
One possible prior art could be the use of software-based memoization techniques in optimizing loop execution in computer systems.
Unanswered Questions
How does this hardware-driven memoization technique compare to software-based memoization techniques in terms of performance and efficiency?
The article does not provide a direct comparison between hardware-driven memoization and software-based memoization techniques in terms of performance and efficiency.
What are the potential limitations or drawbacks of implementing this hardware-driven memoization technique in existing systems?
The article does not address any potential limitations or drawbacks of implementing this hardware-driven memoization technique in existing systems.
Original Abstract Submitted
methods and apparatus for instruction elimination through hardware driven memoization of loop instances. a hardware-based loop memoization technique learns repeating sequences of loops and transparently removes instructions for the loop instructions from instruction sequences while making their output available to dependent instructions as if the loop instructions had been executed. a path-based predictor is implemented at the front-end to predict these loop instances and remove their instructions from instruction sequences. a novel memoization prediction micro-operation (uop) is inserted into the instruction sequence for instances of loops that are predicted to be memoized. the memoization prediction uop is used to compare the input signature (expected set of input values for the loop) with the actual signature to determine correct and incorrect predictions. the input signature learnt is based on all live-ins of a loop, both explicit register-based live-ins as well as loads to memory in the loop body that determine code path and outputs.
