Dynamic GPU Cache Control Through Workload Profiling
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Solution Overview
Problem
Choosing optimal cache settings for GPU resources to maximize performance is challenging since the best settings cannot be determined until after the work is completed, leading to suboptimal performance in 3D rendering workloads.
Innovation Solution
A dynamic cache control mechanism that performs software profiling to generate a sector map for critical resources, collects cache hits, and applies cache settings based on profile data using hardware profiling and targeting logic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cache settings are configured before workload execution, then device complexity is reduced and ease of operation is improved, but manufacturing precision of performance optimization is worsened because optimal settings cannot be determined in advance
Solution Approach 1:
The patent performs preliminary software profiling and hardware profiling before final cache configuration to gather statistics about resource access patterns. This preliminary action enables the system to determine optimal cache settings based on actual workload characteristics rather than guessing in advance, thus resolving the contradiction between ease of configuration and precision of optimization.
Solution Approach 2:
The patent implements a feedback mechanism where cache performance is monitored during workload execution, and cache settings are dynamically adjusted based on observed performance metrics. The system uses feedback from hardware profiling data and software profiling data to continuously optimize cache configuration, achieving both ease of operation and high precision performance optimization.
2Manufacturing precision
If cache settings are optimized after workload completion, then manufacturing precision of performance optimization is improved, but loss of time occurs because suboptimal settings were used during execution
Solution Approach 1:
The patent performs profiling and determines optimal cache settings before workload execution begins. By gathering software profiling data and hardware profiling data in advance, the system can configure caches with high precision optimization before the workload starts, eliminating the time loss that would occur with suboptimal settings during execution.
Solution Approach 2:
The patent implements dynamic cache configuration that adapts to different workload types. The system can switch between different cache policies (such as WC and WT policies) based on the specific workload characteristics identified through profiling, allowing optimal performance for each workload type without time loss.
3Productivity
If dynamic cache optimization is implemented, then productivity is improved through better performance, but device complexity increases due to additional profiling and control mechanisms
Solution Approach 1:
The patent segments the cache system into different partitions that can be independently configured with different cache policies. By dividing the cache into segments that can be optimized separately for different workload types, the system achieves high productivity without overwhelming complexity, as each segment can be managed independently based on profiling data.
Solution Approach 2:
The patent implements self-service mechanisms where the system automatically performs profiling, analyzes workload characteristics, and configures optimal cache settings without requiring manual intervention. The hardware and software profiling systems work autonomously to determine and apply the best cache configuration, improving productivity while managing complexity through automation rather than manual control.
Data Source
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AI summary
An apparatus to facilitate dynamic cache control is disclosed. The apparatus includes one or more processors to profile execution characteristics of a graphics workload at a processing resource to generate profile data indicating a quantity of cache hits that occur at a cache memory and apply one or more cache settings to the cache memory based on the profile data.