View source for Nvidia corporation (20240134645). USING A VECTOR PROCESSOR TO CONFIGURE A DIRECT MEMORY ACCESS SYSTEM FOR FEATURE TRACKING OPERATIONS IN A SYSTEM ON A CHIP simplified abstract

=USING A VECTOR PROCESSOR TO CONFIGURE A DIRECT MEMORY ACCESS SYSTEM FOR FEATURE TRACKING OPERATIONS IN A SYSTEM ON A CHIP=


==Organization Name==

[[:Category:nvidia corporation|nvidia corporation]]


[[Category:nvidia corporation]]

==Inventor(s)==

[[:Category:Ahmad Itani of San Jose CA (US)|Ahmad Itani of San Jose CA (US)]][[Category:Ahmad Itani of San Jose CA (US)]]

[[:Category:Yen-Te Shih of Zhubei City (TW)|Yen-Te Shih of Zhubei City (TW)]][[Category:Yen-Te Shih of Zhubei City (TW)]]

[[:Category:Jagadeesh Sankaran of Dublin CA (US)|Jagadeesh Sankaran of Dublin CA (US)]][[Category:Jagadeesh Sankaran of Dublin CA (US)]]

[[:Category:Ravi P Singh of Austin TX (US)|Ravi P Singh of Austin TX (US)]][[Category:Ravi P Singh of Austin TX (US)]]

[[:Category:Ching-Yu Hung of Pleasanton CA (US)|Ching-Yu Hung of Pleasanton CA (US)]][[Category:Ching-Yu Hung of Pleasanton CA (US)]]

==USING A VECTOR PROCESSOR TO CONFIGURE A DIRECT MEMORY ACCESS SYSTEM FOR FEATURE TRACKING OPERATIONS IN A SYSTEM ON A CHIP - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240134645 titled 'USING A VECTOR PROCESSOR TO CONFIGURE A DIRECT MEMORY ACCESS SYSTEM FOR FEATURE TRACKING OPERATIONS IN A SYSTEM ON A CHIP

==Simplified Explanation==

The patent application describes optimizations for a VPU and associated components to improve performance and throughput. Some of the optimizations include a min/max collector, automatic store predication functionality, SIMD data path organization for inter-lane sharing, transposed load/store with stride parameter functionality, load with permute and zero insertion functionality, hardware, logic, and memory layout for two-point and two-by-two point lookups, and per memory bank load caching capabilities. Decoupled accelerators can offload VPU processing tasks, a hardware sequencer in a DMA system reduces programming complexity, and a VPU configuration mode allows for dynamic region-based data movement operations.

* Min/max collector
* Automatic store predication functionality
* SIMD data path organization for inter-lane sharing
* Transposed load/store with stride parameter functionality
* Load with permute and zero insertion functionality
* Hardware, logic, and memory layout for two-point and two-by-two point lookups
* Per memory bank load caching capabilities
* Decoupled accelerators for offloading VPU processing tasks
* Hardware sequencer in a DMA system to reduce programming complexity
* VPU configuration mode for dynamic region-based data movement operations

== Potential Applications ==
The technology described in the patent application could be applied in various fields such as image processing, video encoding/decoding, machine learning, and artificial intelligence.

== Problems Solved ==
This technology solves the problem of improving VPU performance and throughput by implementing various optimizations and offloading processing tasks to decoupled accelerators.

== Benefits ==
The benefits of this technology include increased VPU performance, improved throughput, reduced programming complexity, and enhanced data movement operations.

== Potential Commercial Applications ==
Potential commercial applications of this technology include smartphones, tablets, cameras, drones, autonomous vehicles, and other devices requiring efficient data processing and movement capabilities.

== Possible Prior Art ==
One possible prior art could be the use of SIMD data path organization in processors to improve performance and efficiency. Another could be the use of hardware accelerators to offload processing tasks in computing systems.

=== Unanswered Questions ===

== How does the VPU configuration mode impact overall system performance? ==
The VPU configuration mode allows for dynamic region-based data movement operations without a processing controller. It would be interesting to know how this impacts the overall system performance in terms of speed and efficiency.

== What are the potential limitations of using decoupled accelerators in offloading VPU processing tasks? ==
While decoupled accelerators can improve throughput and performance, there may be limitations such as increased power consumption or added complexity in system design. It would be important to understand these limitations for practical implementation.


==Original Abstract Submitted==

in various examples, a vpu and associated components may be optimized to improve vpu performance and throughput. for example, the vpu may include a min/max collector, automatic store predication functionality, a simd data path organization that allows for inter-lane sharing, a transposed load/store with stride parameter functionality, a load with permute and zero insertion functionality, hardware, logic, and memory layout functionality to allow for two point and two by two point lookups, and per memory bank load caching capabilities. in addition, decoupled accelerators may be used to offload vpu processing tasks to increase throughput and performance, and a hardware sequencer may be included in a dma system to reduce programming complexity of the vpu and the dma system. the dma and vpu may execute a vpu configuration mode that allows the vpu and dma to operate without a processing controller for performing dynamic region based data movement operations.



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