GPU Memory Reconfiguration with Dynamic Cache Bank Assignment
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Solution Overview
Problem
Current graphics processing units (GPUs) face challenges in efficiently managing memory resources due to fixed function computational units and limited flexibility in processing graphics data, leading to suboptimal performance in parallel processing tasks.
Innovation Solution
Implementing dynamic reconfiguration of cache memory bank assignments based on hardware statistics and enabling virtual memory address translation using mixed four kilobyte and 64 kilobyte pages within the same page table hierarchy, along with near and far regions of the cache hierarchy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed function computational units are used in GPUs, then hardware structure is simplified and manufacturing is easier, but memory management flexibility and processing efficiency deteriorate
Solution Approach 1:
The patent implements dynamic reconfiguration of cache memory bank assignments by allowing the memory controller to dynamically allocate and reassign cache memory banks to different memory interfaces based on real-time workload demands. This enables the system to transition from static fixed-function units to dynamic adaptable units, resolving the contradiction between manufacturing simplicity and operational flexibility.
Solution Approach 2:
The patent creates a universal memory management system where cache memory banks can serve multiple functions and multiple memory interfaces simultaneously. The memory controller acts as a universal coordinator that can assign the same cache memory resources to different interfaces (e.g., HBM, GDDR) based on demand, making the hardware structure versatile without requiring separate dedicated units for each interface.
2Device complexity
If fixed cache memory bank assignments are implemented, then device complexity is reduced, but memory management efficiency and processing performance deteriorate
Solution Approach 1:
The system implements dynamic reconfiguration where cache memory bank assignments are not fixed but can be changed in real-time based on workload characteristics. The memory controller continuously monitors usage patterns and reassigns cache banks dynamically, maintaining low complexity control logic while achieving high processing efficiency through adaptive resource allocation.
Solution Approach 2:
The patent changes the parameter of cache memory bank assignments from static to dynamic. By allowing the assignment parameters to change based on workload demands and usage patterns, the system achieves improved memory management efficiency without significantly increasing device complexity, as the changes are managed through software-controlled configuration.
3Device complexity
If uniform cache memory allocation is used, then device complexity is minimized, but adaptability to different workload types and performance deteriorate
Solution Approach 1:
The patent applies local quality by allowing different cache memory banks to be assigned to different memory interfaces based on their specific workload requirements. Each interface can receive cache resources optimized for its particular workload type, creating local adaptations without requiring complete system redesign. The memory controller manages these local allocations efficiently.
Solution Approach 2:
The system transitions from uniform static cache allocation to dynamic adaptive allocation. Cache memory banks can be dynamically reassigned between different interfaces based on real-time workload characteristics, enabling the system to adapt to varying workload types while maintaining relatively simple control mechanisms through the memory controller.
4Ease of operation
If static memory configuration is implemented, then ease of operation is improved, but processing performance and memory utilization efficiency deteriorate
Solution Approach 1:
The patent implements a self-service memory management system where the memory controller automatically monitors workload patterns and performs dynamic reconfiguration of cache memory assignments without requiring manual intervention. The system serves itself by detecting performance bottlenecks and autonomously reallocating resources, maintaining ease of operation while dramatically improving memory utilization efficiency.
Solution Approach 2:
The system allows memory configuration parameters to change dynamically based on workload demands. The memory controller automatically adjusts cache bank assignments, associativity, and other parameters in response to changing conditions, enabling the system to optimize performance automatically without complicating the operational interface or requiring user intervention.
Data Source
AI summary
Embodiments described herein provide techniques to enable the dynamic reconfiguration of memory on a general-purpose graphics processing unit. One embodiment described herein enables dynamic reconfiguration of cache memory bank assignments based on hardware statistics. One embodiment enables for virtual memory address translation using mixed four kilobyte and sixty-four kilobyte pages within the same page table hierarchy and under the same page directory. One embodiment provides for a graphics processor and associated heterogenous processing system having near and far regions of the same level of a cache hierarchy.