3 ms·

100x relative to NumPy is still quite a lot, depending on how much of their code manages to stay in the C extension. If it was pure Python the delta would likel

by oivey 3y ago

100x relative to NumPy is still quite a lot, depending on how much of their code manages to stay in the C extension. If it was pure Python the delta would likely be much, much larger. Julia is definitely built on the shoulders of giants. I don’t have experience with most of those languages, especially in high performance Lisp or Haskell. Calling C++ high level is definitely not in the same vein as Python or Julia. My understanding is that Haskell can run into all sorts of performance gotchas because lazy evaluation can be unpredictable and recursion may not always easily unroll into optimizable loops. I think the combination of features, especially borrowed from Lisp and C++, really come together as something very productive for writing fast, very high level code.

pjmlp 3y ago
C++ is definitely high level, in the same vein as Python and Julia, the only thing missing is reflection (if we ignore C++/CLI, C++ Builder and custom libraries), which with some luck might still make the cut to C++26. Just because some people insist in using it like C, doesn't make it less higher level in available features and tooling. Regardless of how easy it is to optimize Haskell code, even stupid Haskell code beats an interpreted language like Python. And C bindings are not Python, regardless of how the Python community likes to think otherwise. If anything, I look forward to Julia and others to put pressure in the community to take PyPy and other JIT attempts more seriously. Or maybe it doesn't matter and in a couple of years everyone has moved into mojo, if it is successful.
- oivey 3y ago
  I disagree that C++ is high level in the same way. The core of the language’s memory management relying at some level on bare pointers adds complexity that can never be removed. The syntax itself is not simple and rarely has the magic of 1 line of code expanding into an incredibly complex yet simply understandable computation. That functionality cannot even be retrofitted on because its metaprogramming system sucks. PyPy will still never be as fast as C++ because the semantics of Python itself make it hard to compile into efficient code. Funny enough, Haskell has that similar problem that it’s difficult to compile well. That’s the actual magic of Julia: its semantics are designed so it can be compiled to fast code while still being ergonomic like Python. Mojo may end up being good, but in the examples I’ve seen the real “fast” part of the language doesn’t look all that much like Python anyway.
  - pjmlp 3y ago
    As mentioned, some people insist in using C++ as if it was C. Smalltalk, Common Lisp, JavaScript, SELF, Dylan JIT implementations, for highly dynamic languages, beg to differ. Some of those, anything in the process space can change at any time, either by using language features, or stopping into the debugger, changing the world as much as we like, hit continue or retry as if it was still the original code. The Python dynamism as a problem is an excuse from a language culture that sees writing C extensions as being Python code, thus not willing to spend the resources to make it happen. Thankfully even Ruby is leaving Python behind, joining the list of highly dynamic languages with a JIT in the baggage.
    - oivey 3y ago
      No, it’s not just that people write C++ like it’s C. Another example: there is no simple syntax for broadcasting a function over a collection. Anonymous functions have syntax that is all parentheses and brackets. They’re this way because adding them to the language itself would be breaking. You can’t easily improve the syntax of these things yourself for your subset of code because the meta programming systems C++ has just aren’t great compared to Lisp and Lispy languages like Julia. Further, even if you do add a bunch of cool stuff yourself like a GC or some other syntax magic, it rarely composes well with other libraries. Core to this is that inheritance never really panned out as hoped, and templates are cumbersome. C++ has come a long way, but all of that is due to the overall design of the language itself, not just how it is used. Can you write something as fast as BLAS in JavaScript? As far as I know, the answer is no. Python’s dynamism makes it so that a compiler often times can’t do anything to infer what some function calls will do. No investment will completely fix it without breaking changes to the language itself.
      - pjmlp 3y ago
        I suggest learning about C++ ranges and CUDA algorithms. Parenthesis and brackets have nothing to do with how high level a language happens to be. BLAS in JavaScript would certainly be faster than Python, this is what is being discussed here. Again the dynamism excuse. You can change ANYTHING in Smalltalk, SELF, Common Lisp, and their JITs make up for it. Might not be C++ fast by today standards, as those languages don't see much investment nowadays, they certainly beat Python no matter what.

by oivey 3y ago

pjmlp 3y ago

C++ is definitely high level, in the same vein as Python and Julia, the only thing missing is reflection (if we ignore C++/CLI, C++ Builder and custom libraries), which with some luck might still make the cut to C++26. Just because some people insist in using it like C, doesn't make it less higher level in available features and tooling. Regardless of how easy it is to optimize Haskell code, even stupid Haskell code beats an interpreted language like Python. And C bindings are not Python, regardless of how the Python community likes to think otherwise. If anything, I look forward to Julia and others to put pressure in the community to take PyPy and other JIT attempts more seriously. Or maybe it doesn't matter and in a couple of years everyone has moved into mojo, if it is successful.

oivey 3y ago
I disagree that C++ is high level in the same way. The core of the language’s memory management relying at some level on bare pointers adds complexity that can never be removed. The syntax itself is not simple and rarely has the magic of 1 line of code expanding into an incredibly complex yet simply understandable computation. That functionality cannot even be retrofitted on because its metaprogramming system sucks. PyPy will still never be as fast as C++ because the semantics of Python itself make it hard to compile into efficient code. Funny enough, Haskell has that similar problem that it’s difficult to compile well. That’s the actual magic of Julia: its semantics are designed so it can be compiled to fast code while still being ergonomic like Python. Mojo may end up being good, but in the examples I’ve seen the real “fast” part of the language doesn’t look all that much like Python anyway.
- pjmlp 3y ago
  As mentioned, some people insist in using C++ as if it was C. Smalltalk, Common Lisp, JavaScript, SELF, Dylan JIT implementations, for highly dynamic languages, beg to differ. Some of those, anything in the process space can change at any time, either by using language features, or stopping into the debugger, changing the world as much as we like, hit continue or retry as if it was still the original code. The Python dynamism as a problem is an excuse from a language culture that sees writing C extensions as being Python code, thus not willing to spend the resources to make it happen. Thankfully even Ruby is leaving Python behind, joining the list of highly dynamic languages with a JIT in the baggage.
  - oivey 3y ago
    No, it’s not just that people write C++ like it’s C. Another example: there is no simple syntax for broadcasting a function over a collection. Anonymous functions have syntax that is all parentheses and brackets. They’re this way because adding them to the language itself would be breaking. You can’t easily improve the syntax of these things yourself for your subset of code because the meta programming systems C++ has just aren’t great compared to Lisp and Lispy languages like Julia. Further, even if you do add a bunch of cool stuff yourself like a GC or some other syntax magic, it rarely composes well with other libraries. Core to this is that inheritance never really panned out as hoped, and templates are cumbersome. C++ has come a long way, but all of that is due to the overall design of the language itself, not just how it is used. Can you write something as fast as BLAS in JavaScript? As far as I know, the answer is no. Python’s dynamism makes it so that a compiler often times can’t do anything to infer what some function calls will do. No investment will completely fix it without breaking changes to the language itself.
    - pjmlp 3y ago
      I suggest learning about C++ ranges and CUDA algorithms. Parenthesis and brackets have nothing to do with how high level a language happens to be. BLAS in JavaScript would certainly be faster than Python, this is what is being discussed here. Again the dynamism excuse. You can change ANYTHING in Smalltalk, SELF, Common Lisp, and their JITs make up for it. Might not be C++ fast by today standards, as those languages don't see much investment nowadays, they certainly beat Python no matter what.