Question 1

How much faster is Parallel Hashmap than std::unordered_map?

Accepted Answer

Parallel Hashmap is significantly faster, using SSE2 parallel lookups and optimized memory layouts to outperform std::unordered_map by wide margins in both lookup and insertion, especially at high load factors. Benchmarks in the design writeup show consistent speed advantages.

Question 2

How to make Parallel Hashmap thread-safe for concurrent access?

Accepted Answer

Use the parallel hash map variants (e.g., parallel_flat_hash_map) and provide a mutex type like std::mutex as a template parameter. Methods like if_contains() and modify_if() operate safely under submap locks, but standard iterators aren't protected.

Question 3

When should I choose a flat hash map over a node hash map?

Accepted Answer

Pick flat hash maps for better performance and lower memory with small, trivially copyable values. Switch to node hash maps if you need pointer stability or have large values (over 100 bytes) that are costly to move, as noted in the README's decision points.

Question 4

How to serialize a hash map to disk with Parallel Hashmap?

Accepted Answer

Flat hash maps support fast dump/load for trivially copyable data using single-array serialization, which is about 10 times faster than element-wise methods but uses 10-60% extra disk space. See the serialize.cc example for implementation.

Question 5

Parallel Hashmap vs GTL: which one is better?

Accepted Answer

If you're on C++11 to C++17, use Parallel Hashmap for its compatibility and performance. For C++20 or above, switch to GTL as it's the actively developed successor with similar features and modern C++ support, as recommended by the author.

Question 6

How to forward declare Parallel Hashmap containers in my headers?

Accepted Answer

Include phmap_fwd_decl.h to forward declare containers, but note it doesn't work for hash maps with pointer keys, a current limitation. This helps reduce compile times in large projects.

Parallel Hashmap

What is Parallel Hashmap?

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