pairwise_distance f64 emulation

Author: Hardcode84

dpbench/benchmarks/pairwise_distance/pairwise_distance_numba_mlir_k.py

@@ -6,7 +6,7 @@
 import numpy as np
 
 
-@nb.kernel
+@nb.kernel(gpu_fp64_truncate="auto")
 def _pairwise_distance_kernel(X1, X2, D):
     i = nb.get_global_id(0)
 

dpbench/benchmarks/pairwise_distance/pairwise_distance_numba_mlir_n.py

@@ -6,7 +6,7 @@
 import numpy as np
 
 
-@nb.njit(parallel=True, fastmath=True)
+@nb.njit(parallel=True, fastmath=True, gpu_fp64_truncate="auto")
 def _pairwise_distance(X1, X2, D):
     x1 = np.sum(np.square(X1), axis=1)
     x2 = np.sum(np.square(X2), axis=1)

dpbench/benchmarks/pairwise_distance/pairwise_distance_numba_mlir_p.py

@@ -7,7 +7,7 @@
 import numpy as np
 
 
-@nb.njit(parallel=True, fastmath=True)
+@nb.njit(parallel=True, fastmath=True, gpu_fp64_truncate="auto")
 def _pairwise_distance(X1, X2, D):
     """Naïve pairwise distance impl - take an array representing M points in N
     dimensions, and return the M x M matrix of Euclidean distances