GPU Telemetry Pipeline Shared Memory
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Solution Overview
Problem
In cloud gaming scenarios, telemetry data generated by multiple hardware and software components of GPUs is not transferred in real time, leading to high latency and low reliability due to slow arrival or message dropping, and results in disorganization and lost information among numerous telemetry data sources.
Innovation Solution
A computer-implemented method and system that access telemetry events from GPU hardware components, serialize them into specified data structures, store these structures in a shared memory location shared by multiple media application sessions, and provide real-time references to these stored data structures to event consumers, thereby improving data accessibility and reducing processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If telemetry data is transferred using traditional methods through multiple hardware and software components, then comprehensive telemetry collection is achieved, but high latency and low reliability occur due to slow arrival or message dropping
Solution Approach 1:
The patent extracts telemetry data collection from individual hardware and software components and consolidates it into a centralized telemetry collection module. This module directly accesses GPU hardware components and collects telemetry data without relying on intermediate components, thereby reducing latency and improving reliability by eliminating message dropping issues in traditional distributed collection methods
Solution Approach 2:
The patent introduces a shared memory location as an intermediary between the telemetry collection module and multiple media application sessions. Telemetry data is stored in this shared memory and made accessible to all sessions simultaneously, enabling real-time data sharing without the latency and reliability issues of traditional point-to-point transmission through multiple components
2Loss of information
If multiple hardware and software components generate telemetry data independently, then comprehensive monitoring is achieved, but disorganization and lost information occur among the many sources
Solution Approach 1:
The patent merges telemetry data from multiple independent hardware and software components into a unified data structure stored in shared memory. The telemetry collection module consolidates data from various GPU components and organizes it into a structured format that is easily accessible and maintainable, eliminating the disorganization that arises from multiple independent sources
Solution Approach 2:
The patent creates a universal telemetry data structure and shared memory location that serves multiple media application sessions simultaneously. This single organized structure can be accessed by any number of sessions, providing a multi-functional solution that handles telemetry from numerous sources without requiring separate organizational systems for each session or component
3Speed
If telemetry data is stored in shared memory and references are provided to event consumers, then real-time accessibility is improved, but memory management complexity increases
Solution Approach 1:
The patent implements a self-service memory management system where the shared memory location automatically manages telemetry data storage and retrieval. Event consumers simply access the shared memory using provided references without requiring complex manual management, and the system automatically handles data organization, memory allocation, and concurrent access coordination
Solution Approach 2:
The patent uses reference copying instead of data copying. Multiple event consumers receive references (pointers) to the same shared memory location rather than copies of the actual telemetry data. This allows real-time access for multiple consumers while avoiding the memory management complexity of duplicating large amounts of telemetry data across multiple locations
Data Source
AI summary
The disclosed computer-implemented method includes accessing telemetry events generated by one or more hardware components of a graphics processing unit (GPU) as part of a graphics generation process, serializing the accessed telemetry events into one or more specified data structures, storing the specified data structures associated with the serialized events in a shared memory location that is shared by multiple concurrently running media application sessions, and providing, in real time, a reference to the stored data structures associated with the serialized events in the shared memory location to specified event consumers. Various other methods, systems, and computer-readable media are also disclosed.