GPU Performance Tracking via Architectural Abstraction
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Solution Overview
Problem
Existing GPU performance tracking tools are often vendor-specific and lack interoperability, making it difficult to accurately track and compare the resource utilization of GPUs from different manufacturers, which can lead to inefficiencies in rendering graphics and video streams.
Innovation Solution
A method and computing device that obtain data on the hierarchy of architectural units of a GPU, associate threads with specific SIMD modules, and display resource utilization through an interface, allowing for consistent tracking across different GPUs by using manufacturer-defined nomenclature and transforming architectural data for interoperability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vendor-specific GPU performance tracking tools are used, then accurate tracking for a specific GPU type is achieved, but interoperability with GPUs from different manufacturers is lost
Solution Approach 1:
The patent creates a universal performance tracking system that can monitor multiple GPU vendors through a common interface. The abstraction layer translates vendor-specific architectural data into a standardized format, allowing a single tool to track performance across different GPU manufacturers without requiring separate vendor-specific tools for each.
Solution Approach 2:
The patent introduces an intermediary abstraction layer between the GPU hardware and the performance tracking tool. This intermediary translates vendor-specific architectural hierarchies and nomenclature into a standardized representation, enabling the tracking tool to interface with multiple GPU vendors without direct vendor-specific integration.
2Measurement precision
If multiple vendor-specific tools are used to track different GPU manufacturers, then accurate tracking for each vendor is achieved, but system complexity increases
Solution Approach 1:
The patent merges multiple vendor-specific tracking tools into a single unified performance tracking system. By combining the functionality of multiple specialized tools into one system with a universal interface, it reduces the number of separate tools needed while maintaining the ability to accurately track performance across different GPU vendors.
Solution Approach 2:
The unified tracking tool is designed with multi-functionality to handle multiple GPU vendors through a common interface. The system can adapt to different vendor architectures and translate them into a standardized format, eliminating the need for separate specialized tools for each vendor.
3Loss of information
If vendor-specific architectural nomenclature is used, then accurate representation of GPU architecture is achieved, but comparison across different GPUs becomes difficult
Solution Approach 1:
The patent transforms vendor-specific architectural parameters and nomenclature into standardized parameters that enable cross-vendor comparison. The system changes the representation of architectural data from proprietary formats to a universal format while preserving the essential architectural characteristics needed for accurate performance analysis and comparison.
Solution Approach 2:
The abstraction layer acts as an intermediary that receives detailed vendor-specific architectural information and translates it into a standardized representation. This intermediary process preserves architectural accuracy for tracking purposes while enabling normalized comparison across different GPU vendors through consistent parameter naming and structure.
Data Source
AI summary
Examples described herein generally relate to indicating resource utilization by a graphics processing unit (GPU). Data indicating a hierarchy of architectural units for executing processing threads on a GPU can be obtained. An indication of a slot assigned to a collection of threads for executing on the GPU can be received, where the slot is associated with a single instruction multiple data (SIMD) module capable of concurrently executing multiple collections of threads. An architectural unit to which the slot is assigned can be determined based on the data indicating the hierarchy of architectural units. An indication of the architectural unit as executing the collection of threads can be outputted.