Direct Cache Transfer Mechanism for Producer-Consumer Data Coherency
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Solution Overview
Problem
In heterogeneous processing environments, existing CPU-Accelerator systems face inefficiencies in data transfer between caches due to reliance on software coherency or hardware coherency mechanisms, leading to delayed data transfer opportunities and cache capacity conflicts, especially in CC-NUMA systems with asymmetric cache sizes and operating frequencies.
Innovation Solution
Implementing Direct Cache Transfer (DCT) mechanisms that initiate data transfer from the producer cache to the consumer cache at the time of data eviction, using new Cache Maintenance Operations (CMOs) like flush-stash and CopyBack-stash, allowing the producer to proactively transfer data without relying on consumer-initiated pull models, thereby avoiding main memory access and optimizing data flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software coherency or hardware coherency mechanisms are used for data transfer between caches, then data coherency is maintained, but data transfer latency increases and transfer opportunities are delayed
Solution Approach 1:
The patent implements proactive data transfer by monitoring cache capacity utilization in advance. When the producer cache approaches capacity thresholds or experiences victim cache lines, the system initiates data transfer to the consumer cache before the producer needs the cache space. This preliminary action eliminates waiting time for consumer-initiated requests while maintaining coherency through controlled cache maintenance operations.
2Reliability
If data is transferred only when consumer requests it, then cache capacity conflicts are avoided, but data transfer opportunities are delayed and bandwidth utilization is reduced
Solution Approach 1:
The system proactively transfers data to the consumer cache before the consumer needs it, based on monitoring producer cache capacity utilization. This preliminary action fills the consumer cache in advance, transforming idle bandwidth into productive data transfer and eliminating subsequent wait times, thereby improving overall data transfer efficiency without causing cache conflicts.
Solution Approach 2:
The patent implements a feedback mechanism where the consumer cache controller monitors its own cache capacity and the producer cache status. This feedback loop enables the consumer to understand when data is available or being transferred, allowing it to adjust its request timing and avoid capacity conflicts while maximizing bandwidth utilization through coordinated transfers.
3Ease of operation
If the consumer initiates data transfer requests, then data is transferred only when needed, but transfer latency increases and bandwidth bottlenecks occur
Solution Approach 1:
The system proactively transfers data to the consumer cache before the consumer issues requests, based on monitoring producer cache capacity utilization. This preliminary action ensures data is already in the consumer cache when needed, eliminating access latency while maintaining the benefit of on-demand retrieval through the consumer's ability to request data when its cache is ready.
4Quantity of substance
If the producer cache size is increased to store more processed data, then more data can be transferred directly, but cache capacity conflicts increase and system complexity grows
Solution Approach 1:
The patent implements asymmetric cache capacity thresholds tailored to each producer-consumer pair's specific workload characteristics and data access patterns. Instead of using a uniform cache size or threshold for all pairs, the system configures local thresholds that optimize data transfer timing for each specific relationship, reducing capacity conflicts and improving transfer efficiency without increasing overall system complexity.
Data Source
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AI summary
The embodiments herein creates DCT mechanisms that initiate a DCT at the time the updated data is being evicted from the producer cache (125). These DCT mechanisms are applied when the producer is replacing the updated contents in its cache because the producer has either moved on to working on a different data set (e.g., a different task) or moved on to working on a different function, or when the producer-consumer task manager (e.g., a management unit) enforces software coherency by sending Cache Maintenance Operations (CMO). One advantage of the DCT mechanism is that because the direct cache transfer takes place at the time the updated data is being evicted, by the time the consumer begins its task, the updated contents have already been placed in its own cache or another cache within the cache hierarchy.