numba-dpex
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IntelPython
Data Parallel Extension for Numba
This is used to track issues during enabling Mandelbrot test case. - [ ] #1013 - [ ] CFD pass to support function calls inside a dpjit function. - [...
The following reproducer crashes the CFD legalization pass: ```python @dpjit def foo2(a,b): b[:,:,0] = a a1 = dpnp.arange(64) a1 = a1.reshape(4,16) print(a1) b1 = dpnp.empty((4,16,4)) foo2(a1, b1) print(b1) print("---------------------------------") a2...
There is no performance reporting, so we don't know how good we are doing on weekly basis. Proposal: Create github CI, to run dpbench weekly and add performance report to...
Knn workload in dpbench fails since it allocates memory inside prange as shown below. To successfully executee knn, numba-dpex needs to add support for allocating memory inside prange loops. ```...
Numba-dpex generates the following LLVM IR for a one-dimensional vector addition kernel: ``` define internal spir_func i32 @dpex_py_devfn__3C__( i8** nocapture %.ret, i8* %arg.a.0, i8* %arg.a.1, i64 %arg.a.2, i64 %arg.a.3, i64...
- [ ] Analyze the possibility and meaning of being able to call @dppy.kernel decorated functions from other @dppy.kernel, @njit, @vectorize decorated functions. - [ ] https://github.com/IntelPython/numba-dppy/issues/205 - [ ]...
### **High-level objective** - [x] Add initial support of DWARF data #26 ### Fix bugs - [x] GDB fails on "-O0" generated IR Initialize issues with code-generation #39, #285 (Possibly...
Currently dtype must be specified explicitly: b = ndpx.local.array(ls, dtype=a.dtype) c = ndpx.private.array(ls, dtype=a.dtype) For consistency with dpnp need to support the case b = ndpx.local.array(ls) c = ndpx.private.array(ls)
I have a kernel doing polynomial interpolation of a cubic spline. I want spline coefficients to be a global "constant" COEFFICIENTS, which are read-only in dpnp array. Instead of passing...
The list of numpy functions, that exist in numba and must be implementing: - [ ] all - [ ] any - [ ] argsort (via dpnp) - [ ]...
