[quote="Maxwell-Hu, post:1, topic:4347, full:true"] I'm interested in heterogeneous execution on multiple GPU, the basic idea is to schedule different ops to different GPU.
What I expected was: - GPU-0 executes 'sigmoid' and 'tanh' - GPU-1 executes 'nn.dense' However, the result seems that all the operators are executed on GPU-0, as I observed that only the GPU-0 is busy even if I place all ops to the GPU-1 Any comments and suggestions are greatly appreciated.  The code is referenced from [[Heterogeneous execution examle]](https://discuss.tvm.ai/t/relay-homogenous-compilation-example/2539/5?u=maxwell-hu) annotated_ops_list_gpu0 = {"sigmoid", "tanh"} annotated_relay_ops_gpu0 = [tvm.relay.op.get(op) for op in annotated_ops_list_gpu0] annotated_ops_list_gpu1 = {"nn.dense"} annotated_relay_ops_gpu1 = [tvm.relay.op.get(op) for op in annotated_ops_list_gpu1] class ScheduleDense(ExprMutator): def __init__(self, device_0, device_1): self.device_0 = device_0 self.device_1 = device_1 super(ScheduleDense, self).__init__() def visit_call(self, expr): visit = super().visit_call(expr) if expr.op in annotated_relay_ops_gpu0: return relay.annotation.on_device(visit, self.device_1) elif expr.op in annotated_relay_ops_gpu1: return relay.annotation.on_device(visit, self.device_1) else: return visit def schedule_dense_on_gpu(expr): sched = ScheduleDense(tvm.gpu(2), tvm.gpu(1)) return sched.visit(expr) [/quote] Nín hǎo, zhège wèntí jiějuéle ma volume_up 11 / 5000 ## Translation results Hello, is this problem solved? --- [Visit Topic](https://discuss.tvm.apache.org/t/heterogeneous-execution-how-to-use-heterogeneous-execution-on-multiple-gpu/4347/4) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/9e3811e3872eab6071d9ec22c198c3deb3427c230fa757eb4a272510500a6c8e).
