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[WIP] enable rdma for weight sync #314
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001a6b6
enable rdma for weight sync
casteryh 4f73bb3
stash
b389c4d
Merge branch 'main' into rdma
98c849c
Merge branch 'main' into rdma
0e2fef6
inherit env variables in provisioner.py
casteryh 64421c4
modified config
casteryh 197d89e
change config
casteryh b783ceb
add profiling
casteryh 6ff0297
GPU -> CUDA
casteryh 9beab76
fix profiler
casteryh 1005314
fix profiler path
casteryh f9491db
parallelize
casteryh b5f307b
fix
casteryh 032021d
Merge branch 'main' into rdma
casteryh 82d8ecd
env var for cpu-bound operation perf
casteryh 0f414dd
fix bad merge
casteryh 8e3174f
fix bad merge
casteryh 05de3e7
temp fix
casteryh 55ecef3
disable prof
casteryh 6d27c86
fix bad merge
casteryh e47493c
sequential put
casteryh 8e792c1
revert
casteryh 40148c5
change default to False for dcp
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is this a bad thing? I thought we were writing it to CPU memory anyways on the trainer put side
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theoretically we don't need this extra copy if RDMA on GPU is working. yes we are writing to cpu memory, but currently it is local gpu-> local cpu-> remote cpu.
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Why is the GPU RDMA not working?
What the perf penalty is with the GPU-CPU copy?
Also, what's the corresponding access on the read side?
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Memory registration error. This could be a build issue but I doubt we have enough time to debug. CPU should work now.
Not sure, need profiling. I'd guess anywhere between 30% - 100% increased latency.
On the read side, it's basically remote cpu -> local cpu -> gpu (vllm worker).