ARM CMN600/CMN700 SF Size and Cache Performance Relationship
The ARM CMN600 and CMN700 interconnect fabrics are critical components in modern System-on-Chip (SoC) designs, particularly when optimizing performance for multi-core ARM Cortex processors. The SF (System Cache) size configuration is a key parameter that directly impacts the performance of the system, especially when dealing with RN-F (Request Node-Full) cache coherence and data transfers. The recommendation in the CMN600 technical reference manual to set the SF size to twice the total exclusive cache size for all RN-Fs is not arbitrary but rooted in the architectural requirements of the cache coherence protocol and the behavior of modern workloads.
The SF acts as a shared cache resource that maintains coherence across multiple RN-F nodes. Each RN-F typically represents a processor cluster or a device with its own local cache hierarchy. The exclusive cache size refers to the portion of the cache that is not shared with other RN-Fs, meaning it holds unique data for that specific node. When the SF size is set to twice the total exclusive cache size, it ensures that the SF can accommodate not only the current working set of data but also additional data that may be evicted from the RN-F caches during high contention or bursty workloads.
This requirement arises from the way cache lines are managed in a coherent system. When a cache line is evicted from an RN-F’s local cache, it must be written back to the SF if it is dirty (modified). If the SF is too small to accommodate these evictions, the system may experience performance degradation due to increased latency in handling cache line evictions and potential thrashing. By doubling the SF size relative to the total exclusive cache size, the system ensures that there is sufficient headroom to handle these evictions efficiently, even under peak load conditions.
Cache Thrashing and Memory Bandwidth Saturation Risks
One of the primary reasons for the SF size recommendation is to mitigate the risk of cache thrashing and memory bandwidth saturation. Cache thrashing occurs when the working set of data exceeds the available cache capacity, causing frequent evictions and reloads of cache lines. This behavior can significantly degrade system performance, as each eviction and reload incurs additional latency and consumes memory bandwidth.
In a system with multiple RN-Fs, each node may have its own working set of data that is actively being accessed and modified. If the SF size is only equal to the total exclusive cache size, the system may quickly run out of space to accommodate evicted cache lines from all RN-Fs simultaneously. This scenario can lead to contention for SF resources, increased latency, and reduced overall system performance.
Memory bandwidth saturation is another critical factor. When the SF is undersized, the system may need to frequently write back evicted cache lines to main memory, consuming valuable memory bandwidth. This can create a bottleneck, especially in systems with high core counts or demanding workloads. By doubling the SF size, the system can absorb more evictions locally within the SF, reducing the frequency of writebacks to main memory and preserving memory bandwidth for other operations.
Optimizing SF Size Configuration and System Performance
To ensure optimal performance, it is essential to configure the SF size correctly based on the specific requirements of the system and workload. The following steps outline a systematic approach to determining and validating the appropriate SF size:
First, calculate the total exclusive cache size for all RN-Fs in the system. This value represents the sum of the exclusive cache sizes for each RN-F node. For example, if there are four RN-Fs, each with an 8MB exclusive cache, the total exclusive cache size would be 32MB.
Next, set the SF size to twice the total exclusive cache size, as recommended by the CMN600 technical reference manual. In the example above, this would result in an SF size of 64MB. This configuration provides sufficient headroom to handle cache line evictions and reduces the risk of cache thrashing and memory bandwidth saturation.
Once the SF size is configured, it is crucial to validate the system’s performance under realistic workloads. Use performance monitoring tools to track key metrics such as cache hit rates, memory bandwidth utilization, and latency. If the system exhibits signs of cache thrashing or memory bandwidth saturation, consider increasing the SF size further or optimizing the workload distribution across RN-Fs.
In addition to configuring the SF size, other factors can influence system performance. For example, the placement of frequently accessed data in the cache hierarchy can impact cache hit rates and overall performance. Use cache partitioning and data placement techniques to ensure that critical data remains in the cache for as long as possible, reducing the need for evictions and reloads.
Finally, consider the impact of system scaling on SF size requirements. As the number of RN-Fs or the size of their exclusive caches increases, the SF size must be adjusted accordingly to maintain optimal performance. Regularly review and update the SF size configuration as the system evolves to ensure continued performance and scalability.
By following these steps and understanding the underlying principles of cache coherence and memory bandwidth management, system designers can optimize the performance of ARM-based systems using the CMN600 and CMN700 interconnect fabrics. Proper configuration of the SF size is a critical aspect of this optimization, ensuring that the system can handle the demands of modern workloads while maintaining low latency and high throughput.
