Multi-Core Producer-Consumer Cache Prefetching
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Solution Overview
Problem
In multi-core systems, the inefficiencies in producer-consumer communication due to multiple address translations required for data access between producer and consumer processes lead to reduced system performance, as consumer processes need to perform extensive memory lookups and cache misses.
Innovation Solution
Executing a producer process on one core to produce data elements and multiple consumer processes on different cores, where one instance of the consumer process consumes data while another instance pre-fetches subsequent data elements into its local cache, avoiding additional time for lengthy address translations and cache misses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple consumer processes are executed on different cores to enable parallelism, then system throughput is improved, but the complexity of managing producer-consumer communication and data translations increases
Solution Approach 1:
The system segments consumer processes across multiple processor cores, with each core executing a dedicated consumer process that handles specific data elements. This segmentation enables parallel processing while isolating communication management to per-core level, reducing overall system complexity.
Solution Approach 2:
The patent introduces a producer process as an intermediary that manages data production and distribution to multiple consumer processes. The producer acts as a mediator that coordinates data flow between different consumer processes on different cores, simplifying the communication management complexity.
2Ease of operation
If consumer processes perform multiple address translations to access shared memory, then data can be accessed from producer process, but time for data access increases due to extensive memory lookups
Solution Approach 1:
The system performs preliminary address translations and data loading into cache memory before the consumer process needs to access the data. By pre-translating addresses and pre-loading data into cache, the actual data access time is significantly reduced as no lengthy address translations are needed during the consumption operation.
Solution Approach 2:
The patent implements prior cushioning by maintaining cache memory buffers that are pre-filled with data elements before consumption. This cushioning mechanism ensures that when data is needed, it is already available in fast cache memory, eliminating the time-consuming memory lookup operations that would otherwise occur.
3Device complexity
If a single consumer process handles all data elements sequentially, then data access is simple, but system throughput is limited by sequential processing
Solution Approach 1:
The system segments the consumer process into multiple instances distributed across different processor cores. Each core executes a dedicated consumer process that handles specific data elements in parallel, dramatically increasing throughput while maintaining relatively simple per-core execution logic.
Solution Approach 2:
The patent transitions from sequential single-core processing to parallel multi-core processing by adding the temporal dimension of concurrent execution. Multiple consumer processes operate simultaneously on different cores, converting a one-dimensional sequential workflow into a multi-dimensional parallel execution model that significantly boosts throughput.
Data Source
AI summary
A novel technique for improving throughput in a multi-core system (and in a virtual machine environment) in which data is processed according to a producer-consumer relationship by eliminating latencies caused by compulsory cache misses. A producer process is executed on one processor core and two or more instances of a consumer process are executed on different cores so that while the first instance of a consumer process is executed in a “consuming” mode to process a first subset of data elements produced by the producer process, a second instance of the consumer process pre-fetches, to its cache memory, a second subset of data items produced by the producer process. As a result, the second subset of data items is already cached at the core where the second instance is running even before the consumer process starts processing the second subset of data items.