Cache misses

Definition

Cache misses occur when the data requested by the CPU is not found in the cache memory, forcing it to fetch data from slower main memory. This event negatively impacts system performance since accessing data from the cache is much faster than retrieving it from RAM. Cache misses are an important performance metric that can reveal how effectively a system is using its cache, influencing overall processing speed and efficiency.

5 Must Know Facts For Your Next Test

1. Cache misses are generally categorized into three types: compulsory (or cold), capacity, and conflict misses, each representing different causes for the miss.
2. Compulsory misses occur when data is accessed for the first time and is not yet loaded into the cache.
3. Capacity misses happen when the cache cannot hold all the data needed for a running program, leading to some data being evicted.
4. Conflict misses arise in set-associative or direct-mapped caches when multiple data entries compete for the same cache slot, causing inefficient use of cache space.
5. Reducing cache misses can significantly enhance system performance, as it minimizes delays caused by fetching data from slower memory sources.

Review Questions

• How do different types of cache misses affect overall system performance?
  • Different types of cache misses—compulsory, capacity, and conflict—impact system performance in various ways. Compulsory misses slow down performance mainly during the initial phases of a program when data is being loaded for the first time. Capacity misses indicate that the cache is too small for the workload, leading to frequent replacements and longer access times. Conflict misses show inefficient utilization of cache space due to competing data requests, which can further degrade performance.
• Discuss how locality of reference contributes to minimizing cache misses in computing systems.
  • Locality of reference plays a crucial role in reducing cache misses by predicting which data will be accessed next based on previous access patterns. Temporal locality suggests that recently accessed data is likely to be accessed again soon, while spatial locality indicates that data near recently accessed locations may also be needed. By leveraging these principles, caches can prefetch relevant data, leading to a higher chance of hits and fewer misses overall.
• Evaluate strategies that can be implemented to reduce cache misses and enhance caching efficiency.
  • To reduce cache misses and improve caching efficiency, several strategies can be employed. Increasing cache size can help accommodate more data and reduce capacity misses. Implementing advanced caching algorithms such as least-recently-used (LRU) can minimize conflict misses by tracking usage patterns effectively. Additionally, optimizing software to improve locality of reference through techniques like loop blocking or data structure alignment can further decrease the likelihood of cache misses, leading to better overall system performance.

Related terms

Cache hit: A cache hit occurs when the requested data is found in the cache, allowing for faster data retrieval compared to fetching from main memory.

Cache coherence: Cache coherence refers to the consistency of data stored in multiple cache levels, ensuring that changes in one cache are reflected in others to avoid stale data.

Locality of reference: Locality of reference is a principle that states programs tend to access a relatively small portion of memory repeatedly, which helps improve cache performance.