On Fri, Feb 22, 2013 at 1:56 PM, Костя Лопухин <kostia.lopu...@gmail.com> wrote: > Yes, it had a little loop that was setting arguments for a function > call, now the call is inlined, thank you! But in the inlined code > there is immidately "call_assembler", followed by a "keepalive" of the > frame. Does it have an equally simple answer? Or it has to do with the > function arguments?
call_assembler means that the function you call has a loop (such functions are not inlined, only a part of it), so you end up with a call. IF you call a simpler function with no loops, the call will disappear > > 2013/2/22 Maciej Fijalkowski <fij...@gmail.com>: >> On Fri, Feb 22, 2013 at 8:49 AM, Костя Лопухин <kostia.lopu...@gmail.com> >> wrote: >>> In what cases does the jit decide not to inline a function call, but >>> place "call_may_force" instead? >>> The context is that I have a simple interpreter, like an expanded >>> kermit, and I am testing how the jit helps - it perfectly unboxes >>> wrapped objects in a loop, but does not inline function calls - I >>> wonder what am I missing here. I found a place where PyPy interpreter >>> makes a call and did not see anything special there. >> >> call_may_force means you call a function that has a loop that calls >> back to the intepreter. Probably argument handling or so. You need to >> annotate the function with @jit.unroll_safe (that means that each time >> the number of iteration is different, you'll get slightly different >> assembler, so beware) > > > 2013/2/22 Maciej Fijalkowski <fij...@gmail.com>: >> On Fri, Feb 22, 2013 at 8:49 AM, Костя Лопухин <kostia.lopu...@gmail.com> >> wrote: >>> In what cases does the jit decide not to inline a function call, but >>> place "call_may_force" instead? >>> The context is that I have a simple interpreter, like an expanded >>> kermit, and I am testing how the jit helps - it perfectly unboxes >>> wrapped objects in a loop, but does not inline function calls - I >>> wonder what am I missing here. I found a place where PyPy interpreter >>> makes a call and did not see anything special there. >> >> call_may_force means you call a function that has a loop that calls >> back to the intepreter. Probably argument handling or so. You need to >> annotate the function with @jit.unroll_safe (that means that each time >> the number of iteration is different, you'll get slightly different >> assembler, so beware) > > > 2013/2/22 Maciej Fijalkowski <fij...@gmail.com>: >> On Fri, Feb 22, 2013 at 8:49 AM, Костя Лопухин <kostia.lopu...@gmail.com> >> wrote: >>> In what cases does the jit decide not to inline a function call, but >>> place "call_may_force" instead? >>> The context is that I have a simple interpreter, like an expanded >>> kermit, and I am testing how the jit helps - it perfectly unboxes >>> wrapped objects in a loop, but does not inline function calls - I >>> wonder what am I missing here. I found a place where PyPy interpreter >>> makes a call and did not see anything special there. >> >> call_may_force means you call a function that has a loop that calls >> back to the intepreter. Probably argument handling or so. You need to >> annotate the function with @jit.unroll_safe (that means that each time >> the number of iteration is different, you'll get slightly different >> assembler, so beware) _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
