Multi-bank Cache for Vector Memory Access
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Solution Overview
Problem
Current cache systems, particularly in SIMD operations, face performance bottlenecks due to limitations in single-bank cache architectures, where only one cache line can be retrieved per cycle, limiting the simultaneous access to multiple cache lines required for vector memory access requests.
Innovation Solution
Implementing a multi-bank cache architecture where cache lines are evenly distributed across multiple banks to allow simultaneous access to cache lines from different banks, with a cache controller that determines bank allocation priorities to maximize bandwidth by spreading cache line allocations across banks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single-bank cache architecture is used, then the cache structure is simple and easy to implement, but only one cache line can be retrieved per cycle, limiting memory access bandwidth
Solution Approach 1:
The cache is divided into multiple independent banks, where each bank can independently store and retrieve cache lines. This segmentation allows parallel access to multiple cache lines simultaneously, increasing memory access bandwidth from one line per cycle to multiple lines per cycle, directly resolving the bandwidth limitation of single-bank architectures.
2Productivity
If cache lines are accessed sequentially in a single bank, then the access control is simple, but vector memory access requests cannot be serviced efficiently
Solution Approach 1:
By segmenting the cache into multiple banks, the system can service vector memory access requests that require simultaneous access to multiple cache lines. Each bank independently handles portions of the vector request, enabling efficient parallel servicing without complex sequential control logic.
Solution Approach 2:
The cache controller dynamically allocates cache lines to different banks based on the access pattern and request type. For vector memory access requests, the controller distributes cache line allocations across multiple banks to maximize parallel access efficiency, adapting the access strategy to the specific operation requirements.
Data Source
AI summary
Techniques are disclosed for processing cache operations. The techniques include determining a set of cache lines that include data for a vector memory access request; determining bank allocation priorities for the set of cache lines, wherein the bank allocation priorities are chosen to result in the set of cache lines being evenly distributed among the banks; determining actual banks for the set of cache lines; and accessing the cache lines in one or more access iterations, wherein at least one of the one or more access iterations includes accessing multiple cache lines in different banks at the same time.