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/allgather_barrier.py

@@ -0,0 +1,55 @@
+import argparse
+from mscclpp.language import *
+from mscclpp.language.buffer import Buffer
+from mscclpp.language.collectives import AllGather
+from mscclpp.language.types import ChannelType, ReplicationPolicy
+
+
+def allgather_test(gpus, instances):
+    """
+    Demonstrates how to use barrier in the MSCCL++ DSL with an allgather collective.
+    This example uses an allpairs algorithm for the allgather operation.
+    Steps:
+    1. Each rank sends a chunk to all other ranks' output buffers and copies the chunk to its own output buffer.
+    2. A barrier is called to synchronize the send and copy operations, and signal peers that the data has been sent.
+    3. Wait for all the chunks from other ranks to be received.
+    """
+    size = gpus
+    collective = AllGather(size, 1, False)
+    with MSCCLPPProgram(
+        "allgather_with_barrier",
+        collective,
+        size,
+        instances,
+        protocol="Simple",
+        replication_policy=ReplicationPolicy.interleaved,
+    ):
+        for n in range(gpus):
+            c = chunk(n, Buffer.input, 0, 1)
+            for peer in range(gpus):
+                if n != peer:
+                    c.put(peer, Buffer.output, n, sendtb=peer, chan_type=ChannelType.sm)
+                else:
+                    c.copy(n, Buffer.output, n, sendtb=peer)
+            # explicit barrier
+            r = rank(n)
+            r.barrier(tb_list=list(range(gpus)))
+            for peer in range(gpus):
+                if n != peer:
+                    c.signal(peer, Buffer.output, n, sendtb=peer, chan_type=ChannelType.sm)
+
+        for n in range(gpus):
+            for peer in range(gpus):
+                c = chunk(n, Buffer.output, peer, 1)
+                if n != peer:
+                    c.wait(peer, Buffer.input, peer, recvtb=peer, chan_type=ChannelType.sm)
+
+        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()
+allgather_test(args.num_gpus, args.instances)