Add GpuBuffer class (#423)

* Renamed and moved mem alloc functions into the `mscclpp::detail::`
namespace (now `mscclpp::detail::gpuCalloc*<T>()`)
* Deprecated constructor-calling mem alloc functions
(`mscclpp::makeShared*<T>()` and `mscclpp::makeUnique*<T>()`)
* Added a new `mscclpp::GpuBuffer<T>()` class that should be used in
general for allocating communication buffers
* Added a new `mscclpp.utils.GpuBuffer` Python class that inherits
`cupy.ndarray` and allocates using `mscclpp::gpuMemAlloc`
* Renamed `mscclpp::memcpyCuda*<T>()` functions into
`mscclpp::gpuMemcpy*<T>()` for name consistency
* A few fixes in NVLS memory allocation
* Tackled minor compiler warnings

docs/getting-started/tutorials/python-api.md

@@ -14,6 +14,7 @@ from mscclpp import (
     ProxyService,
     Transport,
 )
+from mscclpp.utils import GpuBuffer
 import mscclpp.comm as mscclpp_comm
 
 def create_connection(group: mscclpp_comm.CommGroup, transport: str):
@@ -32,7 +33,7 @@ if __name__ == "__main__":
     mscclpp_group = mscclpp_comm.CommGroup(MPI.COMM_WORLD)
     connections = create_connection(mscclpp_group, "NVLink")
     nelems = 1024
-    memory = cp.zeros(nelem, dtype=cp.int32)
+    memory = GpuBuffer(nelem, dtype=cp.int32)
     proxy_service = ProxyService()
     simple_channels = group.make_proxy_channels(proxy_service, memory, connections)
     proxy_service.start_proxy()