CPcppbert3·May 5, 2020
reply of the author
https://github.com/ExaScience/elprep-bench/issues/3
In Comparison of C++17, Go, and Java for a next-generation sequencing toolExaScience
elprep-bench
C++2020–2020
ExaScience / elprep-bench
elprep-bench
elPrep reimplementations in C++ and Java, only for benchmark comparisons
5Distinct people
5Mentions
0Explicit recommenders
10GitHub stars
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What it is
elPrep reimplementations in C++ and Java, only for benchmark comparisons
GitHub
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
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HN mentions by day5 dated mentions
Observed mentions: 2020-04-23 17:00:15 UTC to 2020-05-05 08:07:09 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Apr 23 | 2020-04-23 00:00:00 UTC | 2020-04-24 00:00:00 UTC | 4 | 0 | 4 |
| Apr 24 | 2020-04-24 00:00:00 UTC | 2020-04-25 00:00:00 UTC | 0 | 0 | 0 |
| Apr 25 | 2020-04-25 00:00:00 UTC | 2020-04-26 00:00:00 UTC | 0 | 0 | 0 |
| Apr 26 | 2020-04-26 00:00:00 UTC | 2020-04-27 00:00:00 UTC | 0 | 0 | 0 |
| Apr 27 | 2020-04-27 00:00:00 UTC | 2020-04-28 00:00:00 UTC | 0 | 0 | 0 |
| Apr 28 | 2020-04-28 00:00:00 UTC | 2020-04-29 00:00:00 UTC | 0 | 0 | 0 |
| Apr 29 | 2020-04-29 00:00:00 UTC | 2020-04-30 00:00:00 UTC | 0 | 0 | 0 |
| Apr 30 | 2020-04-30 00:00:00 UTC | 2020-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 1 | 2020-05-01 00:00:00 UTC | 2020-05-02 00:00:00 UTC | 0 | 0 | 0 |
| May 2 | 2020-05-02 00:00:00 UTC | 2020-05-03 00:00:00 UTC | 0 | 0 | 0 |
| May 3 | 2020-05-03 00:00:00 UTC | 2020-05-04 00:00:00 UTC | 0 | 0 | 0 |
| May 4 | 2020-05-04 00:00:00 UTC | 2020-05-05 00:00:00 UTC | 0 | 0 | 0 |
| May 5 | 2020-05-05 00:00:00 UTC | 2020-05-06 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
5 sourcesIt would be interesting to see an output of the compiler flags used in the C++ program that was benchmarked. The build script doesn't set an optimization level so it would default to -O0:
https://github.com/ExaScience/elprep-bench/blob/master/cpp/m...
I am sure they didn't benchmark it like this but it would be interesting to see the flags that /were/ used.
In Comparison of C++17, Go, and Java for a next-generation sequencing toolAfter quickly glancing the code, I concluded that they wrote C++ like there is no static type. It seems they faithfully ported the very dynamic nature of their existing code to C++ without thinking.
Like what is this?
https://github.com/ExaScience/elprep-bench/blob/master/cpp/f...
auto alns = any_cast<shared_ptr<deque<shared_ptr<sam_alignment>>>>(data);
So the data is sam_alignment type inside shared_ptr inside deque inside another share_ptr inside god forbid any? Why did they do that? What kind of abomination is this? Also from the context, it is the only possible type. they use:
try { any_cast<abomination_type>(data) ; }
catch ( bad_any_cast ) { throw runtime_error(...) ; }
If you're so sure an object of any only hold exactly one type and everything else is unexpected error, you shouldn't use any at all!
They really like std::de
Read the rest
que<T> and use it everywhere even though the sizeof(T) is like a few dozen bytes at best so they should rather use std::vector. The data structure of deque is a list of array. while it can amortize the continious adding of the elements to front or back, since the element size is very small, they should rather use vector.
Speaking of data structure, they also use std::unordered_map<int, any>. the unordered_map is very slow(it's a node based hash map, not suitable for the modern hardware) and the sizeof(int) + sizeof(any) is like 20 bytes(sizeof(int) + two pointers) so they got no benefit of using node based data structure here. They should rather use sorted vector and binary search it.
My conclusion, it's slow because they wrote C++ like a dynamic typed language and they choose the wrong data structures.
I had a quick look at the C++ source code provided at https://github.com/ExaScience/elprep-bench/tree/master/cpp.
As suspected, everything is dynamically allocated and no memory mapping (see e.g. http://man7.org/linux/man-pages/man2/mmap.2.html) is used. No wonder this is slow and eats a lot of memory. At the moment I have no information about why this design was chosen, if there is a justification for it, or if the developers only knew this option. Maybe I can find some hints in the paper. From what I've seen up to now it can be savely assumed that with optimal use of data structures and system functions the C++ results are at least one order of magnitude better.
In Comparison of C++17, Go, and Java for a next-generation sequencing toolthe source code: https://github.com/ExaScience/elprep-bench
In Comparison of C++17, Go, and Java for a next-generation sequencing tool