Segmented Branch Target Buffers by Branch Type to Reduce Front-End Stalls
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Solution Overview
Problem
Conventional Branch Target Buffers (BTBs) in processors suffer from misprediction penalties due to high code-footprint workloads, leading to performance issues related to front-end stalls and re-steering, as they do not optimize for the varying behavior and locality of different branch instruction types.
Innovation Solution
A segmented BTB structure is implemented with separate caches for different branch types, including a hot cache for frequent direct branches and a target cache for less frequent indirect branches, utilizing branch type information and hint fields in the instruction set architecture to optimize allocation and reduce miss rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conventional single-structure BTB is used, then the device complexity is low, but the misprediction penalty increases and performance deteriorates
Solution Approach 1:
The BTB is divided into multiple independent memory structures (first memory structure and second memory structure) that store branch target information for different branch instruction types separately. This segmentation allows each structure to be optimized for specific branch types, reducing misprediction penalties while maintaining manageable complexity through modular design
Solution Approach 2:
Different portions of the BTB are assigned different characteristics based on branch instruction types. The first memory structure handles direct branches with specific storage patterns, while the second memory structure handles indirect branches differently. This local optimization improves overall performance by tailoring storage characteristics to specific operational needs
2Productivity
If the BTB size is increased to reduce misprediction penalties, then the performance improves, but the storage requirements and device complexity increase
Solution Approach 1:
By segmenting the BTB into multiple memory structures, the patent achieves better prediction accuracy without proportionally increasing total storage capacity. Each segmented structure can be smaller but more efficient, as they store only the specific branch types they handle, reducing overall storage requirements compared to a single large structure
Solution Approach 2:
The patent changes the organizational parameters of the BTB by introducing multiple memory structures with different access patterns and storage characteristics. This allows optimization of hit rates and prediction accuracy without linearly increasing storage capacity, as each structure operates with tailored parameters for its specific branch type
Data Source
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AI summary
In one embodiment, a processor includes a branch predictor to predict whether a branch instruction is to be taken and a branch target buffer (BTB) coupled to the branch predictor. The branch target buffer may be segmented into a first cache portion and a second cache portion, where, in response to an indication that the branch is to be taken, the BTB is to access an entry in one of the first cache portion and the second cache portion based at least in part on a type of the branch instruction, an occurrence frequency of the branch instruction, and spatial information regarding a distance between a target address of a target of the branch instruction and an address of the branch instruction. Other embodiments are described and claimed.