Adding upstream version 124.0.1.upstream/124.0.1

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+# Machine code analysis tools
+
+## The microarchitecture of modern CPUs
+
+While you might have heard of Instruction Set Architectures, such as `x86` or
+`arm` or `mips`, the term _microarchitecture_ (also written here as _µ-arch_),
+refers to the internal details of an actual family of CPUs, such as Intel's
+_Haswell_ or AMD's _Jaguar_.
+
+Replacing scalar code with SIMD code will improve performance on all CPUs
+supporting the required vector extensions.
+However, due to microarchitectural differences, the actual speed-up at
+runtime might vary.
+
+**Example**: a simple example arises when optimizing for AMD K8 CPUs.
+The assembly generated for an empty function should look like this:
+
+```asm
+nop
+ret
+```
+
+The `nop` is used to align the `ret` instruction for better performance.
+However, the compiler will actually generated the following code:
+
+```asm
+repz ret
+```
+
+The `repz` instruction will repeat the following instruction until a certain
+condition. Of course, in this situation, the function will simply immediately
+return, and the `ret` instruction is still aligned.
+However, AMD K8's branch predictor performs better with the latter code.
+
+For those looking to absolutely maximize performance for a certain target µ-arch,
+you will have to read some CPU manuals, or ask the compiler to do it for you
+with `-C target-cpu`.
+
+### Summary of CPU internals
+
+Modern processors are able to execute instructions out-of-order for better performance,
+by utilizing tricks such as [branch prediction], [instruction pipelining],
+or [superscalar execution].
+
+[branch prediction]: https://en.wikipedia.org/wiki/Branch_predictor
+[instruction pipelining]: https://en.wikipedia.org/wiki/Instruction_pipelining
+[superscalar execution]: https://en.wikipedia.org/wiki/Superscalar_processor
+
+SIMD instructions are also subject to these optimizations, meaning it can get pretty
+difficult to determine where the slowdown happens.
+For example, if the profiler reports a store operation is slow, one of two things
+could be happening:
+
+- the store is limited by the CPU's memory bandwidth, which is actually an ideal
+  scenario, all things considered;
+
+- memory bandwidth is nowhere near its peak, but the value to be stored is at the
+  end of a long chain of operations, and this store is where the profiler
+  encountered the pipeline stall;
+
+Since most profilers are simple tools which don't understand the subtleties of
+instruction scheduling, you
+
+## Analyzing the machine code
+
+Certain tools have knowledge of internal CPU microarchitecture, i.e. they know
+
+- how many physical [register files] a CPU actually has
+
+- what is the latency / throughtput of an instruction
+
+- what [µ-ops] are generated for a set of instructions
+
+and many other architectural details.
+
+[register files]: https://en.wikipedia.org/wiki/Register_file
+[µ-ops]: https://en.wikipedia.org/wiki/Micro-operation
+
+These tools are therefore able to provide accurate information as to why some
+instructions are inefficient, and where the bottleneck is.
+
+The disadvantage is that the output of these tools requires advanced knowledge
+of the target architecture to understand, i.e. they **cannot** point out what
+the cause of the issue is explicitly.
+
+## Intel's Architecture Code Analyzer (IACA)
+
+[IACA] is a free tool offered by Intel for analyzing the performance of various
+computational kernels.
+
+Being a proprietary, closed source tool, it _only_ supports Intel's µ-arches.
+
+[IACA]: https://software.intel.com/en-us/articles/intel-architecture-code-analyzer
+
+## llvm-mca
+
+<!--
+TODO: once LLVM 7 gets released, write a chapter on using llvm-mca
+with SIMD disassembly.
+-->