Merge mscclpp-lang to mscclpp project (#442)

First step to merge msccl-tools into mscclpp repo. In this step will
move all msccl related code, pass the current tests and do some
necessary refactor.

Add `mscclpp.language` module
Add `_InstructionOptimizer` and `DagOptimizer` class to optimize the dag
Add `DagLower` to lower dag to intermediate representation 
Add documents for mscclpp.language
Remove msccl related code

python/examples/allreduce_ring.py

@@ -0,0 +1,59 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+import argparse
+from mscclpp.language import *
+from mscclpp.language.collectives import AllReduce
+from mscclpp.language.buffer import Buffer
+
+
+def allreduce_ring(size, instances):
+    """
+    Implements a ring based allreduce.
+    Steps:
+    1. Send signal to next rank and wait for signal from previous rank. Make sure the data is ready in previous rank.
+    2. Reduce the data and send to next rank.
+    3. After all the data is reduced, propagate the data to all the ranks.
+    """
+    collective = AllReduce(size, size, True)
+    with MSCCLPPProgram(
+        f"allreduce_ring",
+        collective,
+        size,
+        instances,
+        protocol="Simple",
+    ):
+        # Reduce ring
+        for step in range(0, size - 1):
+            for index in range(0, size):
+                rank = (index + step) % size
+                next_rank = (index + step + 1) % size
+                c = chunk(rank, Buffer.input, index)
+                c.signal(next_rank, Buffer.input, index, 0)
+                prev_rank = (index + step - 1) % size
+                c = chunk(rank, Buffer.input, (index + size - 1) % size)
+                c.wait(prev_rank, Buffer.input, (index + size - 1) % size, 0)
+                c.reduce(chunk(prev_rank, Buffer.input, (index + size - 1) % size), recvtb=0)
+
+        # Propagate ring
+        for step in range(-1, size - 2):
+            for index in range(0, size):
+                rank = (index + step) % size
+                c = chunk(rank, Buffer.input, index)
+                next_rank = (index + step + 1) % size
+                c.put(next_rank, Buffer.input, index, sendtb=0)
+                c.signal(next_rank, Buffer.input, index, 0)
+                prev_rank = (index + step - 1) % size
+                c = chunk(rank, Buffer.input, (index + size - 1) % size)
+                c.wait(prev_rank, Buffer.input, (index + size - 1) % size, 0)
+
+        Json()
+        Check()
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("num_gpus", type=int, help="number of gpus")
+parser.add_argument("instances", type=int, help="number of instances")
+args = parser.parse_args()
+
+allreduce_ring(args.num_gpus, args.instances)