cuda.nvbench -> cuda.bench

Per PR review suggestion:
   - `cuda.parallel`    - device-wide algorithms/Thrust
   - `cuda.cooperative` - Cooperative algorithsm/CUB
   - `cuda.bench`       - Benchmarking/NVBench

python/examples/cutlass_gemm.py

@@ -17,19 +17,19 @@
 
 import sys
 
+import cuda.bench as bench
 import cuda.bindings.driver as driver
 import cuda.core.experimental as core
-import cuda.nvbench as nvbench
 import cupy as cp
 import cutlass
 import numpy as np
 
 
-def as_bindings_Stream(cs: nvbench.CudaStream) -> driver.CUstream:
+def as_bindings_Stream(cs: bench.CudaStream) -> driver.CUstream:
     return driver.CUstream(cs.addressof())
 
 
-def as_core_Stream(cs: nvbench.CudaStream) -> core.Stream:
+def as_core_Stream(cs: bench.CudaStream) -> core.Stream:
     return core.Stream.from_handle(cs.addressof())
 
 
@@ -47,7 +47,7 @@ def make_cp_array(
     )
 
 
-def cutlass_gemm(state: nvbench.State) -> None:
+def cutlass_gemm(state: bench.State) -> None:
     n = state.get_int64("N")
     r = state.get_int64("R")
 
@@ -96,7 +96,7 @@ def cutlass_gemm(state: nvbench.State) -> None:
     # warm-up to ensure compilation is not timed
     plan.run(stream=s)
 
-    def launcher(launch: nvbench.Launch) -> None:
+    def launcher(launch: bench.Launch) -> None:
         s = as_bindings_Stream(launch.get_stream())
         plan.run(stream=s, sync=False)
 
@@ -104,10 +104,10 @@ def cutlass_gemm(state: nvbench.State) -> None:
 
 
 if __name__ == "__main__":
-    gemm_b = nvbench.register(cutlass_gemm)
+    gemm_b = bench.register(cutlass_gemm)
     gemm_b.add_int64_axis("R", [16, 64, 256])
     gemm_b.add_int64_axis("N", [256, 512, 1024, 2048])
 
     gemm_b.add_float64_axis("alpha", [1e-2])
 
-    nvbench.run_all_benchmarks(sys.argv)
+    bench.run_all_benchmarks(sys.argv)