Comments (2)
Please see the llama multiprocess example. The multi-GPU inference is used to create parellelized linear layers:
candle/candle-examples/examples/llama_multiprocess/model.rs
Lines 293 to 308 in f48c07e
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Please see the llama multiprocess example. The multi-GPU inference is used to create parellelized linear layers:
candle/candle-examples/examples/llama_multiprocess/model.rs
Lines 293 to 308 in f48c07e
That example is for a single node. How about multiple nodes? Can we just run the example with mpirun -n 2 --hostfile ../../hostfile target/release/llama_multiprocess 2 2000
Update:
I guess I must modify the code to support the world rank for MPI. I think sticking to NCCL as a backend might be better, but then is there support in Cudarc for cross-node communication?
Found this library https://github.com/oddity-ai/async-cuda
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