Hi!
I wanted to try and load graphs in a parallel manner to speed things up 
i tried to use the code snippet below:
import joblib
from functools import partial
import dgl
def load_graphs_chunk(graphs_idxs, bin_path):
graphs, labels_dict = dgl.load_graphs(bin_path, graphs_idxs)
return graphs
# Constants
graphs_count = 411
graphs_load_chunks_size = 5
graph_dataset_path = "/some/path/to/file.bin"
# Extract relevant idxs chunks
graphs_idx_chunks = [list(range(idx, idx + graphs_load_chunks_size)) for idx in range(0, graphs_count, graphs_load_chunks_size)]
# Prepare functions for parallel work
run_func = partial(load_graphs_chunk, bin_path=graph_dataset_path)
jobs = (joblib.delayed(run_func)(graphs_idxs) for graphs_idxs in graphs_idx_chunks)
# Execute parallel jobs
res = joblib.Parallel(n_jobs=20, verbose=10)(jobs)
Where the file in graph_dataset_path is a bin file created with dgl.save_graphs.
But unfortunately, i get an error 
tried with several different bin files with different content and get the same.
My graphs are heterographs - it seem relevant from the stack trace.
Also its seem that the functions did executed and finish because i get the progress messages from joblib:
Using backend: pytorch
[Parallel(n_jobs=20)]: Using backend LokyBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done 1 tasks | elapsed: 1.0s
[Parallel(n_jobs=20)]: Done 10 tasks | elapsed: 1.3s
[Parallel(n_jobs=20)]: Done 21 tasks | elapsed: 1.7s
[Parallel(n_jobs=20)]: Done 32 tasks | elapsed: 2.0s
[Parallel(n_jobs=20)]: Done 53 out of 83 | elapsed: 2.7s remaining: 1.5s
[Parallel(n_jobs=20)]: Done 62 out of 83 | elapsed: 2.9s remaining: 1.0s
[Parallel(n_jobs=20)]: Done 71 out of 83 | elapsed: 3.3s remaining: 0.6s
[Parallel(n_jobs=20)]: Done 80 out of 83 | elapsed: 3.7s remaining: 0.1s
And after that, I get an exception.
For context - Iām using dgl 0.6.0post1 without CUDA.
Would love for your help 
Here is the thrown exception:
---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "anonymized/lib/python3.8/site-packages/joblib/externals/loky/process_executor.py", line 431, in _process_worker
r = call_item()
File "anonymized/python3.8/site-packages/joblib/externals/loky/process_executor.py", line 285, in __call__
return self.fn(*self.args, **self.kwargs)
File "anonymized/python3.8/site-packages/joblib/_parallel_backends.py", line 595, in __call__
return self.func(*args, **kwargs)
File "anonymized/python3.8/site-packages/joblib/parallel.py", line 262, in __call__
return [func(*args, **kwargs)
File "anonymized/python3.8/site-packages/joblib/parallel.py", line 262, in <listcomp>
return [func(*args, **kwargs)
File "<ipython-input-2-d4e22f518813>", line 6, in load_graphs_chunk
File "anonymized/python3.8/site-packages/dgl/data/graph_serialize.py", line 182, in load_graphs
return load_graph_v2(filename, idx_list)
File "anonymized/python3.8/site-packages/dgl/data/graph_serialize.py", line 192, in load_graph_v2
heterograph_list = _CAPI_LoadGraphFiles_V2(filename, idx_list)
File "dgl/_ffi/_cython/./function.pxi", line 287, in dgl._ffi._cy3.core.FunctionBase.__call__
File "dgl/_ffi/_cython/./function.pxi", line 222, in dgl._ffi._cy3.core.FuncCall
File "dgl/_ffi/_cython/./function.pxi", line 211, in dgl._ffi._cy3.core.FuncCall3
File "dgl/_ffi/_cython/./base.pxi", line 155, in dgl._ffi._cy3.core.CALL
dgl._ffi.base.DGLError: [21:01:07] /opt/dgl/src/graph/heterograph.cc:509: Check failed: magicNum == kDGLSerialize_HeteroGraph (3458765063554631570 vs. 15949673719616654015) : Invalid HeteroGraph Data
Stack trace:
[bt] (0) anonymized/python3.8/site-packages/dgl/libdgl.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x4f) [0x7fa8d00a513f]
[bt] (1) anonymized/python3.8/site-packages/dgl/libdgl.so(dgl::HeteroGraph::Load(dmlc::Stream*)+0x151) [0x7fa8d07e79c1]
[bt] (2) anonymized/python3.8/site-packages/dgl/libdgl.so(dgl::serialize::LoadHeteroGraphs(std::string const&, std::vector<unsigned long, std::allocator<unsigned long> >)+0x7ea) [0x7fa8d086d56a]
[bt] (3) anonymized/python3.8/site-packages/dgl/libdgl.so(+0x9d842f) [0x7fa8d086642f]
[bt] (4) anonymized/python3.8/site-packages/dgl/libdgl.so(DGLFuncCall+0x48) [0x7fa8d0781d38]
[bt] (5) anonymized/python3.8/site-packages/dgl/_ffi/_cy3/core.cpython-38-x86_64-linux-gnu.so(+0x15f89) [0x7fa8cf7c7f89]
[bt] (6) anonymized/python3.8/site-packages/dgl/_ffi/_cy3/core.cpython-38-x86_64-linux-gnu.so(+0x1626b) [0x7fa8cf7c826b]
[bt] (7) anonymized/python(_PyObject_MakeTpCall+0x22f) [0x55d927b7e85f]
[bt] (8) anonymized/python(_PyEval_EvalFrameDefault+0x475) [0x55d927c01e35]
"""
The above exception was the direct cause of the following exception:
DGLError Traceback (most recent call last)
<ipython-input-2-d4e22f518813> in <module>
20
21 # Execute parallel jobs
---> 22 res = joblib.Parallel(n_jobs=20, verbose=10)(jobs)
anonymized/python3.8/site-packages/joblib/parallel.py in __call__(self, iterable)
1052
1053 with self._backend.retrieval_context():
-> 1054 self.retrieve()
1055 # Make sure that we get a last message telling us we are done
1056 elapsed_time = time.time() - self._start_time
anonymized/python3.8/site-packages/joblib/parallel.py in retrieve(self)
931 try:
932 if getattr(self._backend, 'supports_timeout', False):
--> 933 self._output.extend(job.get(timeout=self.timeout))
934 else:
935 self._output.extend(job.get())
anonymized/python3.8/site-packages/joblib/_parallel_backends.py in wrap_future_result(future, timeout)
540 AsyncResults.get from multiprocessing."""
541 try:
--> 542 return future.result(timeout=timeout)
543 except CfTimeoutError as e:
544 raise TimeoutError from e
anonymized/python3.8/concurrent/futures/_base.py in result(self, timeout)
430 raise CancelledError()
431 elif self._state == FINISHED:
--> 432 return self.__get_result()
433
434 self._condition.wait(timeout)
anonymized/python3.8/concurrent/futures/_base.py in __get_result(self)