Constant Memory Segmentation for Low-Latency GPU Cache Fetching
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Solution Overview
Problem
Current methods for storing constants in on-chip cache for GPUs result in high latency, increased missing constants, and inefficient data fetching, especially in systems with larger constant memory or shared GPUs.
Innovation Solution
Partitioning constant memory into segments and storing only the necessary data in the cache memory based on application needs, using identifier data to determine which segments to fetch and store.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data from constant memory is fetched and stored in on-chip cache before kernel launch, then constants are available in cache, but unnecessary data is fetched increasing cache usage and potentially affecting other applications
Solution Approach 1:
The constant memory is divided into multiple segments, each containing specific constants. The system then selectively fetches only the segments needed by the current kernel, rather than fetching all data. This segmentation allows precise control over what data is cached, reducing unnecessary data transfer while ensuring required constants are available.
Solution Approach 2:
Different segments of constant memory are treated differently based on their usage characteristics. The system identifies which segments are actually needed by the current application and fetches only those, while leaving other segments in constant memory. This localizes the caching operation to only the necessary portions, improving efficiency.
2Quantity of substance
If constants are fetched on-demand when missing from cache, then cache is kept small, but latency increases and performance decreases
Solution Approach 1:
The system performs preliminary analysis to determine which constant segments are needed before kernel launch, and fetches those segments in advance during a preparation phase. This preliminary action ensures that when the kernel executes, the required constants are already in cache, eliminating latency that would otherwise occur from on-demand fetching.
3Quantity of substance
If larger constant memory is used to accommodate more data, then more constants can be stored, but the problem of fetching unnecessary data worsens
Solution Approach 1:
By segmenting the larger constant memory into manageable portions, the system can efficiently navigate and select only the relevant segments for each kernel execution. This segmentation structure enables the system to leverage the larger total capacity while maintaining efficient, selective fetching behavior that avoids the penalties of transferring unnecessary data.
Data Source
AI summary
In various examples, constant memory segmentation for autonomous systems and applications is described herein. Systems and methods are disclosed that partition a constant memory into a number of segments. In some examples, the constant memory is partitioned into equally sized segments while, in some examples, the constant memory is partitioned into varying sized segments. The systems and methods may then use the segments in order to store only a portion(s) of the data from the constant memory in a cache memory (e.g., an on-chip cache). For instance, if an application(s) (e.g., a kernel(s) executing a portion of the application) uses only a portion(s) of the data from the constant memory, then the segments may be used to store the portion(s) of the data from the constant memory in the cache memory without storing another portion(s) of the data from the constant memory in the cache memory.