Dynamic Page Table Entry Sizing for TLB Optimization
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Solution Overview
Problem
Current graphics processing systems face limitations in efficiently processing graphics data due to reliance on fixed function units and lack of parallel processing capabilities, particularly in handling complex graphics operations and machine-learning tasks.
Innovation Solution
A graphics processing unit (GPU) is integrated with host/processor cores to accelerate graphics and machine-learning operations, utilizing a parallel processor architecture with SIMT architecture and dedicated circuitry for efficient processing of commands and instructions, enabling widespread parallel processing across multiple clusters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed function computational units are used to process graphics data, then processing reliability is maintained, but processing efficiency and parallel processing capability are limited
Solution Approach 1:
The patent implements a hybrid architecture where fixed function units handle specific graphics operations while programmable processing clusters handle general-purpose computations. This dynamic configuration allows the system to adapt between specialized and general processing modes, resolving the contradiction between reliability of fixed function units and efficiency of parallel processing.
Solution Approach 2:
The processing clusters are designed with universal programmable units that can execute various types of computations including graphics operations, machine learning tasks, and general-purpose parallel computations. This multi-functionality allows a single architectural element to replace multiple specialized units, improving overall system efficiency.
2Productivity
If traditional graphics processor architecture is used, then device complexity is kept manageable, but parallel processing capability for complex graphics operations is insufficient
Solution Approach 1:
The processor is divided into multiple independent processing clusters, each capable of executing threads in parallel. This segmentation allows the system to achieve high parallel processing capability while keeping each individual cluster's complexity manageable. Each cluster can be independently configured and optimized for specific tasks.
3Productivity
If fixed page size is used in page table entries, then memory management simplicity is maintained, but memory utilization efficiency deteriorates due to inability to handle variable-sized memory allocations
Solution Approach 1:
The page table entry structure is enhanced with dynamic fields that allow the page size to be variable rather than fixed. The PTE includes a page size field that can indicate different page sizes (e.g., 4KB, 64KB, 2MB, 512MB), enabling the memory management system to adapt to different allocation requirements and improve memory utilization efficiency.
Data Source
AI summary
In accordance with one embodiment each page table entry maps a variable page size (per entry), if multiple continuous virtual pages map to contiguous physical pages. This may drastically reduce the number of translation lookaside buffer (TLB) entries needed since each entry can potentially map a larger chunk of memory, in some embodiments.