Peripheral Device Firmware for GPU Command Queue Latency
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Solution Overview
Problem
Current computing systems experience significant latency when processing data from peripheral devices, such as cameras, due to numerous interactions at the application level among OS components, device drivers, and CPU, which degrades performance and fails to meet user expectations for real-time, low-latency applications.
Innovation Solution
The integration of peripheral devices and compute devices at the hardware level, with intelligence added to their firmware, allows for direct communication through a common memory pool, reducing the need for application-level interactions and minimizing CPU response time variability by pre-compiling compute instructions and using a GPU command queue for processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data processing is performed through multiple application-level interactions among OS components, device drivers, and CPU, then system functionality is maintained, but latency increases significantly
Solution Approach 1:
The patent merges the peripheral device and compute device into a tightly integrated unit with shared memory space. The peripheral device can directly access the compute device's memory and processing resources without going through multiple OS-level interactions, thereby reducing latency while maintaining system functionality.
Solution Approach 2:
The patent introduces a shared memory pool as an intermediary between the peripheral device and compute device. This common memory space allows direct data exchange without requiring application-level mediation, reducing the number of interaction steps and associated latency.
2Reliability
If CPU response time is used to process peripheral device data, then general processing capability is maintained, but variable response time degrades application performance
Solution Approach 1:
The patent segments the processing function by dedicating a specific compute device (such as a GPU) to handle peripheral device data processing independently from the CPU. This segmentation ensures consistent processing timing unaffected by CPU workload variations, improving both reliability and productivity.
Solution Approach 2:
The compute device autonomously processes data from the peripheral device using its own processing resources, independent of CPU availability. This self-service capability ensures consistent and predictable response times while maintaining high processing throughput.
3Speed
If peripheral device firmware is enhanced with pre-compiled compute code, then processing speed is improved, but device complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-compiling compute instructions and storing them in the peripheral device's firmware before actual data processing occurs. This allows the peripheral device to quickly execute pre-prepared processing routines without needing to compile code at runtime, thereby achieving high processing speed with acceptable firmware complexity.
Data Source
AI summary
Methods, systems, and computer program products are provided for minimizing latency in a implementation where a peripheral device is used as a capture device and a compute device such as a GPU processes the captured data in a computing environment. In embodiments, a peripheral device and GPU are tightly integrated and communicate at a hardware/firmware level. Peripheral device firmware can determine and store compute instructions specifically for the GPU, in a command queue. The compute instructions in the command queue are understood and consumed by firmware of the GPU. The compute instructions include but are not limited to generating low latency visual feedback for presentation to a display screen, and detecting the presence of gestures to be converted to OS messages that can be utilized by any application.