Write-Combine Buffer Partitioning for Weakly Ordered Memory Writes
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Solution Overview
Problem
Existing write combine buffers in processors are inefficient in utilizing memory resources due to weak ordering and suboptimal partitioning, leading to frequent delays and underutilization of buffer capacity.
Innovation Solution
Implementing a processor with a write-combine buffer that partitions data into smaller segments based on the size of incoming data blocks, allowing dynamic adjustment of partition sizes and initiating draining based on data content, thereby optimizing buffer utilization and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a write-combine buffer is used to temporarily hold data before writing to main memory, then memory access efficiency is improved, but buffer utilization is insufficient due to weak ordering and suboptimal partitioning
Solution Approach 1:
The write-combine buffer is divided into multiple partitions, where each partition can independently store and manage data blocks. This segmentation allows different partitions to handle different data access patterns simultaneously, improving overall buffer utilization by preventing the entire buffer from being idle due to ordering constraints on a single data stream.
Solution Approach 2:
The buffer partitioning structure enables dynamic allocation and management of buffer spaces. Partitions can be selectively activated or deactivated based on actual data access patterns and ordering requirements, allowing the buffer to adaptively optimize its utilization rather than being constrained by static, suboptimal partitioning.
2Device complexity
If data is written to a single buffer without partitioning, then device complexity is reduced, but throughput is limited due to frequent delays from weak ordering
Solution Approach 1:
By segmenting the buffer into multiple independent partitions, the system can process multiple data streams in parallel without being constrained by ordering requirements within a single buffer. This increases throughput by allowing simultaneous writes to different partitions, while the added complexity remains manageable through standardized partition management logic.
3Device complexity
If the buffer is partitioned based on fixed sizes, then device complexity is reduced, but adaptability to varying data block sizes is poor
Solution Approach 1:
The partitioning scheme allows partition sizes and configurations to be dynamically adjusted based on the actual size and characteristics of incoming data blocks. This adaptability enables the buffer to efficiently handle varying data block sizes without requiring complex fixed-size partitioning logic, as partitions can be created, merged, or resized to match the data being processed.
Data Source
AI summary
A processor includes a data buffer, the data buffer being configured as a write-combine buffer. The processor further includes logic circuitry which is configured to perform: receiving, from a further entity, an input data stream for a write operation, wherein the input data stream is received in blocks of data, and partitioning the data buffer into partitions, wherein the partitioning is based on a size of the blocks of data that are received. The logic circuitry is further configured to perform: writing each of the blocks of data to one of the partitions, each block of data being written to a partition of the data buffer based on an address associated with the respective block of data, and for each of the partitions, determining whether to initiate a draining of the respective partition to further memory based on the data that is stored in the respective partition.