Minutes_2022_04_26
Siu Kwan Lam edited this page May 3, 2022
·
1 revision
Attendees: Siu Kwan Lam, LI Da, Nick Riasanovsky, stuart, Shannon Quinn, Andre Masella, Benjamin Graham, Guilherme Leobas, brandon willard, Luk, Graham Markall,
NOTE: All communication is subject to the Numba Code of Conduct.
Please refer to this calendar for the next meeting date.
-
llvmlite clang-format https://github.com/numba/llvmlite/pull/831
-
mission statement discussion deferred to next week
-
#8000 discussion
@njit(locals={"s1": Series, "s2": int64}) def foo(): s1 = pd.Series([1,2,3,4], index=list("ABCD")) s2 = pd.Series([1,2,3,4], index=list("AAAD")) return s1, s2
- if
pd.Series
always returnsSeries
,locals
can force casting to other types (e.g. int64) before storing into variables
- if
-
TODO: mutation of global reference to typedList segfault
-
Emit object files from Numba AOT compiler https://github.com/numba/numba-extras/pull/4
-
Discussion related to https://github.com/numba/numba/pull/6406
def foo_maker():
a = 1
@njit
def foo():
return a
return foo
def foo_maker_2():
a = 1
exec(foo_source, {"a": a})
foo = njit(<load_foo>)
return foo
- #7993 - optimization for frequently used code path
- #7995 - Numba 0.55.1 runtime error with numpy 1.21.6
- #7997 - Indexing a tuple/list of function raises an error
- #7998 - Allow registering and using extra jit options in Numba
- #8002 - CFuncs cannot use numba.carray when jitting is disabled
- #8005 - CUDA print tests do not work on Windows with recent drivers
- #8006 - Call to cuMemFree results in CUDA_ERROR_LAUNCH_TIMEOUT
- #7994 - Supporting multidimensional arrays in quick sort
-
#7996 - Fix binding logic in
@overload_glue
. -
#7999 - Remove
@overload_glue
for NumPy allocators. - **** #8000 - Add flag_class argument in jit decorator
- #8001 - Testhound/fp16 math functions
- #8003 - Add np.broadcast_shapes
- #8004 - CUDA fixes for Windows
- #7992 - Pin llvmlite=0.39.0dev0 builds to build 63 on OSX