Question 1

How does libpopcnt compare to using the built-in __builtin_popcount in GCC?

Accepted Answer

libpopcnt is optimized for arrays and uses advanced SIMD instructions like AVX2, making it much faster for large data sets—benchmarks show speeds over 100 GB/s. For single integers, built-ins might suffice, but libpopcnt excels in bulk operations.

Question 2

Does libpopcnt work on Raspberry Pi or other ARM devices?

Accepted Answer

Yes, libpopcnt supports ARM CPUs with NEON acceleration by default, and with manual compilation flags, it can use SVE on newer chips like AWS Graviton3. It falls back to a portable algorithm if no hardware support is available.

Question 3

How to make libpopcnt use AVX512 on my Intel CPU?

Accepted Answer

Simply compile your program with optimizations enabled (e.g., -O3). libpopcnt automatically detects AVX512 support via CPUID and uses it without extra flags, as stated in the README's 'How it works' section.

Question 4

libpopcnt vs Google's FarmHash for bit counting: which is faster?

Accepted Answer

libpopcnt is specialized for popcount and often faster due to hardware acceleration, while FarmHash is a general-purpose hashing library. For pure bit counting on arrays, libpopcnt is typically superior, but FarmHash might be better if hashing is also needed.

Question 5

How to integrate libpopcnt into my CMake project?

Accepted Answer

Since it's header-only, just add the 'libpopcnt.h' file to your source tree and include it in your code. No CMake configuration is required, but ensure optimizations like -O3 are set in your build flags for best performance.

Question 6

What's the performance overhead of runtime CPU detection in libpopcnt?

Accepted Answer

The overhead is minimal—CPUID is called once on initialization. In benchmarks, this doesn't impact throughput, and if compiled with -march=native, checks are removed entirely for near-native speed.

libpopcnt

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