Exploring How Cache Memory Works
Cache memory, crucial for programmers, stores data inside the CPU for quick access, bridging the CPU-RAM speed gap. Different cache levels vary in speed and capacity, optimizing performance and efficiency.
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This article delves into the intricate workings of cache memory, explaining its importance for programmers. Cache memory, located inside the CPU, stores frequently accessed data for quick retrieval, significantly speeding up processing compared to accessing data from RAM. Different levels of cache (L1, L2, L3) vary in speed and capacity, with L1 being the fastest but smallest. Cache memory is crucial in bridging the speed gap between the CPU and RAM, enhancing processing efficiency. Modern CPUs have separate caches for instructions and data, optimizing performance based on access patterns. Cache placement policies like direct-mapped cache dictate how data is stored in cache blocks. Programmers are advised to write cache-friendly code by optimizing data access patterns for better performance. Understanding cache memory and its nuances is essential for maximizing software efficiency in modern computing environments.
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12 comments[1] https://people.freebsd.org/~lstewart/articles/cpumemory.pdf
[2] https://samueleresca.net/analysis-of-what-every-programmer-s...
cat /sys/devices/system/cpu/cpu0/cache/index0/coherency_line_sizeM2 processors have 128 byte wide cache lines?? That's a big deal. We've been at 64 bytes since what, the Pentium?
It forced you to think in terms of: [array of input data -> operation -> array of intermediate data -> operation -> array of final output data]
Our OOP game engine had to transform their OOP data to array of input data before feeding it into operation, basically a lot of unnecessary memory copies. We had to break objects into "operations", which was not intuitive. But, that got rid a lot of memory copies. Only then we managed to get decent performance.
The good thing, by doing this we also get automatic performance increase on the xbox360 because we were consciously ? unconsciously ? optimizing for cache usage.
A while back I had to create a high speed steaming data processor (not a spark cluster and similar creatures), but a c program that could sit in-line in a high speed data stream and match specific patterns and take actions based on the type of pattern that hit. As part of optimizing for speed and throughput a colleague and I did an obnoxious level of experimentation with read sizes (slurps of data) to minimize io wait queues and memory pressure. Being aligned with the cache-line size, either 1x or 2x was the winner. Good low level close to the hardware c fun for sure.
But otherwise this is a good general overview of how caching is useful.
Not correct. Prefetching has been around for a while, and rather important in optimization.
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