Host IR: add GetCurrentStream
#3605
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wujingyue
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…lap: AG+GEMM layout (#3606) Stacked on top of - [x] #3608 - [x] #3605 # What Lower a MatmulOp sharded on the first inner axis into a pipelined AG+GEMM algorithm achieving fine grained overlap. We introduce a new parallel type `Stream` to account for this scheduling. More precisely, this patch enables lowering the fusion: ``` TensorView* a = makeContigTensor(4); //[S, DIDx(D), M/(S*d), K] TensorView* b = makeContigTensor(2); //[K, N] TensorView* c = matmul(a, b); //[S, D, M/(S*D), N] fusion->addInput(a); fusion->addInput(b); fusion->addOutput(c); auto mesh = DeviceMesh::createForNumDevices(D); a->setDeviceMesh(mesh); b->setDeviceMesh(mesh); c->setDeviceMesh(mesh); a->axis(1)->parallelize(ParallelType::DIDx); c->axis(0)->parallelize(ParallelType::Stream); ``` to the Host Ir program (obtained from dump, using `NVFUSER_DUMP=host_ir`) ``` %HostIrContainer { (T0_g_float[iS0{i0}, ideviceIdx.x1{i2}, iS2{i3}, iS3{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), T1_g_float[iS4{i5}, iS5{i6}] (DeviceMesh{0 1 2 3 4 5 6 7})) -> (T2_g_float[iStream6{i0}, iS7{i2}, iS8{i3}, iS9{i6}, rS10{i4}] (DeviceMesh{0 1 2 3 4 5 6 7})) : GetCurrentStream into Stream 0 T3_g_float[iS11{i0}, iS12{i2}, iS13{i3}, iS14{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}) = ALLOCATE(buffer=T3_g_float[iS11{i0}, iS12{i2}, iS13{i3}, iS14{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), mem_type=global, size=( ( ( i0 * i2 ) * i3 ) * i4 ), zero_init=false, resets_to_zero=fals e) T2_g_float[iStream6{i0}, iS7{i2}, iS8{i3}, iS9{i6}, rS10{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}) = ALLOCATE(buffer=T2_g_float[iStream6{i0}, iS7{i2}, iS8{i3}, iS9{i6}, rS10{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), mem_type=global, size=( ( ( i0 * i2 ) * i3 ) * i6 ), zero_init=fals e, resets_to_zero=false) FOR i104 in iS0{i0}: SetCurrentStream to Stream ( i104 % numberOfStreams ) T4_l_float[ideviceIdx.x15{i2}, iS16{i3}, iS17{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}) = select( T0_g_float[iS0{i0}, ideviceIdx.x1{i2}, iS2{i3}, iS3{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), axis = iS0{i0}, index = i104 ) T5_l_float[iS18{i2}, iS19{i3}, iS20{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}) = select( T3_g_float[iS11{i0}, iS12{i2}, iS13{i3}, iS14{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), axis = iS11{i0}, index = i104 ) Communication 46 (type=Allgather, team=(0 1 2 3 4 5 6 7), input=T4_l_float[ideviceIdx.x15{i2}, iS16{i3}, iS17{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), output=T5_l_float[iS18{i2}, iS19{i3}, iS20{i4}] (DeviceMesh{0 1 2 3 4 5 6 7})) Wait Communication 46 T6_l_float[iS21{i2}, iS22{i3}, iS23{i6}] (DeviceMesh{0 1 2 3 4 5 6 7}) = select( T2_g_float[iStream6{i0}, iS7{i2}, iS8{i3}, iS9{i6}, rS10{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), axis = iStream6{i0}, index = i104 ) T6_l_float[iS21{i2}, iS22{i3}, iS23{i6}] (DeviceMesh{0 1 2 3 4 5 6 7}) = matmul(T5_l_float[iS18{i2}, iS19{i3}, iS20{i4}] (DeviceMesh{0 1 2 3 4 5 6 7}), T1_g_float[iS4{i5}, iS5{i6}] (DeviceMesh{0 1 2 3 4 5 6 7})) SetCurrentStream to Stream 0 Synchronize Stream ( i104 % numberOfStreams ) } // %HostIrContainer ``` The nsight profile shows that we do achieve overlap, in a way that is comparable to the Aten overlap experiments 
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What
adds the primitive
GetCurrentStreamto Host Ir stack.Why
needed for
The idea is that if we want to use multiple stream internally, we need before hand to capture the user stream and to set it back to being the active stream when returning