4 ms·

While I might not agree with the conclusion of the OP, the performance of a programming language should be always paired with its "average" programmers. A lot o

by euske 6y ago

While I might not agree with the conclusion of the OP, the performance of a programming language should be always paired with its "average" programmers. A lot of people tend to straw-man a language they dislike and iron-man (?) a language they like. For an average programmer, I think it might be possible that Java produces a more performant/maintainable code than C++.

tdons 6y ago
An iron man is a triathlon, you are looking for steelman! https://en.wiktionary.org/wiki/steelman https://en.wiktionary.org/wiki/steelman
- PaulDavisThe1st 6y ago
  There is (was?) a Steelman triathlon too (actually, more than one of them, in different parts of the US).
- justincredible 6y ago
  It is also a Black Sabbath song.
carlmr 6y ago
This is very true. I've seen colleagues port Python to C++ and wonder why it's slower. Of course Python is slow, but it will call into efficient C routines for a lot of things that aren't just available out of the box in C++. So what does the average programmer do? They implement their own, inefficient version of this in C++. Now you've saved the overhead of copying your data from the Python to the C-world and back, but the main part of your computations is just not on the level of numpy. So naturally C++ can be much faster than Python, because it doesn't have this overhead, but you have to do it right, which may be more effort.
- mhh__ 6y ago
  For that reason I generally motivate not using python to people on grounds of correctness rather than performance as per se. I can't be bothered to explain how compiler optimizations work so I usually just resort to "it's magic" when it comes to performance. Going from a statically typed language to using python to do number crunching genuinely makes me want to vomit. I don't understand how people convince themselves that it's productive to write so many tests and (say) check types at runtime etc. I actually love Python's syntax but the language design seems like it was thrown together over a weekend.
  - carlmr 6y ago
    >Going from a statically typed language to using python to do number crunching genuinely makes me want to vomit. I don't understand how people convince themselves that it's productive to write so many tests and (say) check types at runtime etc. Totally agree, although I think strong typing is also important, not just static typing. C/C++ has a weak type system because of the automatic conversions it allows. The problem with this discussion however is that the people that push for dynamic languages usually do it because it's "so fast" to do something in Python, and they won't test their software anyway.
  - beagle3 6y ago
    Take a look at Nim if you haven't already - It has a Pythonesque syntax, but strong static typing with extensive user control of semantics you seem to care about; e.g. floats and ints do not convert automatically unless you explicitly "import lenientops"[0] ; You can define 'operational transform' optimizations (such as: c <- c+a\b converts to multiply_accumulate(c,a,b) - which is a big performance difference for e.g matrices) that will be applied by the compiler so that your code shows what you mean (c=c+ab), and yet the compiler gets to compile the efficient version (using the relevant BLAS routine) It's young, but has the best FFI for C,C++,Objective-C or JS you'll find anywhere on one hand, and already a good deal of native implementations, including e.g. a pure Nim BLAS that is comparable to within 5-10% with the best out there (including those with carefully hand optimized ASM kernels). [0] https://nim-lang.org/docs/lenientops.html https://nim-lang.org/docs/lenientops.html
    - 6y ago
- mypalmike 6y ago
  When I moved from C/C++ to Java on the 90s, I was amazed how casually things like hash tables would be used. A single function might create a couple hash tables, do some data juggling and sorting, and solve a problem in like 20 lines of readable, performant code. In my experience, C coders almost invariably employ less performant algorithms and data structures due to the incidental complexity involved in memory allocation, pointer indirection, etc.
  - dehrmann 6y ago
    This is where I always hope a JVM will learn that, use escape analysis to keep things off the heap (they can do this), swap out data structures for more efficient ones for small amounts of data, or tune data structure initialization params (they can't do this).
  - trhway 6y ago
    absolutely. Few years ago i got back deep into C++ after 18 years of mostly Java, and i'm amazed, it is like travel back in time - we (a large C++ platform) are looping over vectors instead of using hashtables/maps, copying strings all the time (we have 4 major types of strings plus some minor ones), and don't get me started on multithreading and locking/synchronization - such an easy and natural thing in Java - even these days the people in C++ world is still seem to be hesitant to use locking and as result of that hesitance push themselves into a myriad of multithreading issues when they risk and/or are forced to use threads. It a sight to behold when a customer waits for that one core/thread to finish the operation on a 400 core 16TB RAM machine - if it were Java all the 400 cores would be burning, the performance would still feel kind of so-so, and the customer would be building up the nerve to upgrade to 800 core 32 TB :) >pointer indirection 30+ years ago, a student at University, i loved how pointers allowed to code algorithms efficiently and expressively compare to the non-pointer languages of the time. In the industry today the situation is completely opposite as correctly noted by the parent.
    - bluGill 6y ago
      In many cases n is small enough that looping over a vector is faster than a hash lookup. The vector loop is very ry cache friendly, while the hash lookup typically involves a cache miss or two.

by euske 6y ago

tdons 6y ago

An iron man is a triathlon, you are looking for steelman! https://en.wiktionary.org/wiki/steelman https://en.wiktionary.org/wiki/steelman

PaulDavisThe1st 6y ago
There is (was?) a Steelman triathlon too (actually, more than one of them, in different parts of the US).
justincredible 6y ago
It is also a Black Sabbath song.

carlmr 6y ago

This is very true. I've seen colleagues port Python to C++ and wonder why it's slower. Of course Python is slow, but it will call into efficient C routines for a lot of things that aren't just available out of the box in C++. So what does the average programmer do? They implement their own, inefficient version of this in C++. Now you've saved the overhead of copying your data from the Python to the C-world and back, but the main part of your computations is just not on the level of numpy. So naturally C++ can be much faster than Python, because it doesn't have this overhead, but you have to do it right, which may be more effort.

mhh__ 6y ago
For that reason I generally motivate not using python to people on grounds of correctness rather than performance as per se. I can't be bothered to explain how compiler optimizations work so I usually just resort to "it's magic" when it comes to performance. Going from a statically typed language to using python to do number crunching genuinely makes me want to vomit. I don't understand how people convince themselves that it's productive to write so many tests and (say) check types at runtime etc. I actually love Python's syntax but the language design seems like it was thrown together over a weekend.
- carlmr 6y ago
  >Going from a statically typed language to using python to do number crunching genuinely makes me want to vomit. I don't understand how people convince themselves that it's productive to write so many tests and (say) check types at runtime etc. Totally agree, although I think strong typing is also important, not just static typing. C/C++ has a weak type system because of the automatic conversions it allows. The problem with this discussion however is that the people that push for dynamic languages usually do it because it's "so fast" to do something in Python, and they won't test their software anyway.
- beagle3 6y ago
  Take a look at Nim if you haven't already - It has a Pythonesque syntax, but strong static typing with extensive user control of semantics you seem to care about; e.g. floats and ints do not convert automatically unless you explicitly "import lenientops"[0] ; You can define 'operational transform' optimizations (such as: c <- c+a\b converts to multiply_accumulate(c,a,b) - which is a big performance difference for e.g matrices) that will be applied by the compiler so that your code shows what you mean (c=c+ab), and yet the compiler gets to compile the efficient version (using the relevant BLAS routine) It's young, but has the best FFI for C,C++,Objective-C or JS you'll find anywhere on one hand, and already a good deal of native implementations, including e.g. a pure Nim BLAS that is comparable to within 5-10% with the best out there (including those with carefully hand optimized ASM kernels). [0] https://nim-lang.org/docs/lenientops.html https://nim-lang.org/docs/lenientops.html
  - 6y ago
mypalmike 6y ago
When I moved from C/C++ to Java on the 90s, I was amazed how casually things like hash tables would be used. A single function might create a couple hash tables, do some data juggling and sorting, and solve a problem in like 20 lines of readable, performant code. In my experience, C coders almost invariably employ less performant algorithms and data structures due to the incidental complexity involved in memory allocation, pointer indirection, etc.
- dehrmann 6y ago
  This is where I always hope a JVM will learn that, use escape analysis to keep things off the heap (they can do this), swap out data structures for more efficient ones for small amounts of data, or tune data structure initialization params (they can't do this).
- trhway 6y ago
  absolutely. Few years ago i got back deep into C++ after 18 years of mostly Java, and i'm amazed, it is like travel back in time - we (a large C++ platform) are looping over vectors instead of using hashtables/maps, copying strings all the time (we have 4 major types of strings plus some minor ones), and don't get me started on multithreading and locking/synchronization - such an easy and natural thing in Java - even these days the people in C++ world is still seem to be hesitant to use locking and as result of that hesitance push themselves into a myriad of multithreading issues when they risk and/or are forced to use threads. It a sight to behold when a customer waits for that one core/thread to finish the operation on a 400 core 16TB RAM machine - if it were Java all the 400 cores would be burning, the performance would still feel kind of so-so, and the customer would be building up the nerve to upgrade to 800 core 32 TB :) >pointer indirection 30+ years ago, a student at University, i loved how pointers allowed to code algorithms efficiently and expressively compare to the non-pointer languages of the time. In the industry today the situation is completely opposite as correctly noted by the parent.
  - bluGill 6y ago
    In many cases n is small enough that looping over a vector is faster than a hash lookup. The vector loop is very ry cache friendly, while the hash lookup typically involves a cache miss or two.