Cache Miss – How to reduce it

While caching is one of the most vital mechanisms for improving site performance, frequent cache misses will increase data access time, resulting in a poor user experience and high bounce rates. This article will help you better understand what a cache miss is, how cache misses work, and how to reduce them.

What is a Cache Miss?

A cache miss happens when the data that a system or application requests to retrieve cannot be found in the cache memory. It is the opposite of a cache hit, where the system successfully retrieves the data it requested from the cache. In the event of a cache miss, the system or app tries to find the data elsewhere, searching the main database for the data it needs. If found in the database, the system usually copies and stores the data in the cache so that the next search for the data is not a cache miss.

Because the primary database is more extensive and slower, searching for data takes more time, which can result in the site experiencing latency and performance issues. Additionally, each cache miss affects the speed of the site and causes a delay, also called a miss penalty. So, minimizing cache misses as much as possible is vital.

What are the reasons?

Cache misses are caused by three primary factors: compulsory, capacity, and conflict miss. Compulsory misses happen when data is fetched for the first time; capacity misses occur when the cache is not large enough to hold all required data; and conflict misses result from the same cache location being replaced by different data items due to limited associativity in the cache.

Types of Cache Misses

Compulsory Miss

A compulsory miss, also known as a cold miss, occurs when data is accessed for the first time. Since the data has not been requested before, it is not present in the cache, leading to a miss. This type of miss is unavoidable as it is inherent in the first reference to the data. The only way to eliminate compulsory misses would be to have an infinite prefetch of data, which is not feasible in real-world systems.

Capacity Miss

A capacity miss happens when the cache cannot contain all the data needed by the system. This type of miss occurs when the working set (the set of data that a program accesses frequently) is larger than the cache size. When the cache is filled to capacity and a new data item is referenced, existing data must be evicted to accommodate the new data, leading to a miss. Capacity misses can be reduced by increasing the cache size or optimizing the program to decrease the size of the working set.

Conflict Miss

Conflict misses, also known as collision misses, occur when multiple data items, which are accessed in a sequence, map to the same cache location, known as a cache set. This type of miss is a result of the cache’s organization. In a set-associative or direct-mapped cache, different data items may be mapped to the same set, leading to conflicts. When a new item is loaded into a filled set, another item must be evicted, leading to a miss if the evicted item is accessed again. Conflict misses can be mitigated by improving the cache’s mapping function or by increasing the cache’s associativity.

Coherence Miss

Coherence misses are specific to multiprocessor systems. In such systems, several processors have their own private caches and access shared data. A coherence miss occurs when one processor updates a data item in its private cache, making the corresponding data item in another processor’s cache stale. When the second processor accesses the stale data, a cache miss occurs. Coherence misses are managed by implementing cache coherence protocols that ensure consistency among the various caches.

The Impact of Cache Misses on Performance

Cache misses have a significant impact on system performance. Whenever a cache miss occurs, the system is compelled to retrieve the desired data from the main memory or another cache at a lower level, which is inherently slower than fetching data from the cache. This delay can lead to a bottleneck in performance, particularly in systems where rapid operations are critical.

For this reason, minimizing cache misses is essential for improving overall system performance in applications where performance is critical, such as real-time systems or high-performance computing.

The frequency of cache misses is due to several factors, including cache size, organization, replacement policy, and data access patterns. Therefore, understanding and effectively avoiding cache miss penalties is an important facet of optimizing system performance.

It is important to note that only some cache misses take the exact toll. For instance, a cache miss stemming from the initial access to a block of data (compulsory miss) is inevitable. On the other hand, cache misses stemming from data displacement for different data (capacity miss) or conflicts in cache placement policies (conflict miss) can be alleviated through meticulous algorithms and system design.

How to reduce Cache Misses

The most effective ways to reduce cache misses and improve cache performance include:

• Optimize Data Locally: Accessing data from local caches allows for smoother, quicker access to the data than doing so from global caches. Localizing your data helps speed things up while minimizing cache misses.
• Enable Data Prefetching: CPU processors can predict which data you might need to fetch from the higher memory storage and move it into a fast-access local cache before you need it — reducing cache misses caused by latency.
• Employ Loop Tiling: Data can be divided into smaller segments — known as blocks or tiles — that fit more easily within the cache. This makes it easier for the CPU to retrieve the data from the caches and reuse it, reducing the number of cache misses.
• Consider Cache Blocking: Users can leverage blocking or blocking-aware software to operate on smaller data blocks that fit within the cache. This reduces cache misses.
• Optimize Cache Size and Associativity: It’s possible to analyze workload characteristics and tailor cache size and associativity to fit the specific needs of the application.
• Optimize Memory Access Patterns: Be sure to align data structures, use proper data structures, and ensure efficient memory accesses to minimize cache misses.
• Utilize Compiler Optimization: Employ compiler optimizations like loop unrolling, software prefetching, and cache-aware optimizations to improve cache utilization and reduce misses.
• Profile and Analyse: Use profiling tools to identify cache miss patterns and performance bottlenecks — enabling targeted optimizations.

Conclusion

Caching enables websites and web apps to improve their performance. Set-associative, fully associative, and direct-mapped cache techniques are three cache mapping approaches that site owners can benefit from. A cache miss occurs when the requested information cannot be found in the cache. The different types of cache misses include compulsory, conflict, coherent, and capacity cache misses.