In this post we introduce a few most common tools used for memory subsystem performance debugging.
We investigate memory loads and stores that the compiler inserts for us without our knowledge: “the compiler’s secret life”. We show that these loads and stores, although necessary for the compiler are not necessary for the correct functioning of our program. And finally, we explain how you can improve the performance of your program by removing them.
In our experiments with the memory access pattern, we have seen that good data locality is a key to good software performance. Accessing memory sequentially and splitting the data set into small-sized pieces which are processed individually improves data locality and software speed. In this post, we will present a few techniques to improve the…
We continue the investigation from the previous post, trying to measure how the memory subsystem affects software performance. We write small programs (kernels) to quantify the effects of cache line, memory latency, TLB cache, cache conflicts, vectorization and branch prediction.
In this post we investigate the memory subsystem of a desktop, server and embedded system from the software viewpoint. We use small kernels to illustrate various aspects of the memory subsystem and how it effects performance and runtime.
We talk about instruction level parallelism: what instruction-level parallelism is, why is it important for your code’s performance and how you can add instruction-level parallelism to improve the performance of your memory-bound program.
We investigate how memory consumption, dataset size and software performance correlate…