Renaming channels

.azure-pipelines/ut.yml

@@ -35,7 +35,7 @@ jobs:
         cmake -DCMAKE_BUILD_TYPE=Release -DMSCCLPP_BYPASS_GPU_CHECK=ON -DMSCCLPP_USE_CUDA=ON ..
         make -j
       workingDirectory: '$(System.DefaultWorkingDirectory)'
-  
+
   - task: DownloadSecureFile@1
     name: SshKeyFile
     displayName: Download key file

README.md

@@ -49,8 +49,8 @@ The following highlights key concepts of MSCCL++.
 MSCCL++ provides peer-to-peer communication methods between GPUs. A peer-to-peer connection between two GPUs is called a *Channel*. Channels are constructed by MSCCL++ host-side interfaces and copied to GPUs during initialization. Channels provide *GPU-side interfaces*, which means that all communication methods are defined as a device function to be called from a GPU kernel code. For example, the `put()` method in the following example copies 1KB data from the local GPU to a remote GPU.
 
 ```cpp
-// `ProxyChannel` will be explained in the following section.
-__device__ mscclpp::DeviceHandle<mscclpp::ProxyChannel> channel;
+// `PortChannel` will be explained in the following section.
+__device__ mscclpp::DeviceHandle<mscclpp::PortChannel> channel;
 __global__ void gpuKernel() {
   ...
   // Only one thread is needed for this method.
@@ -78,15 +78,15 @@ __device__ void barrier() {
 
 MSCCL++ provides consistent interfaces, i.e., the above interfaces are used regardless of the location of the remote GPU (either on the local node or on a remote node) or the underlying link (either NVLink/xGMI or InfiniBand).
 
-### ProxyChannel and SmChannel
+### PortChannel and MemoryChannel
 
-MSCCL++ delivers two types of channels, **ProxyChannel** and **SmChannel**. `ProxyChannel` provides (R)DMA-based data copy and synchronization methods. When called, these methods send/receive a signal to/from a host-side proxy (hence the name `ProxyChannel`), which will trigger (R)DMA (such as `cudaMemcpy*` or `ibv_post_send`) or issue synchronization methods (such as `cudaStreamSynchronize` or `ibv_poll_cq`). Since the key functionalities are run by the proxy, `ProxyChannel` requires only a single GPU thread to call its methods. See all `ProxyChannel` methods from [here](./include/mscclpp/proxy_channel_device.hpp).
+MSCCL++ delivers two types of channels, **PortChannel** and **MemoryChannel**. `PortChannel` provides port-mapping-based data copy and synchronization methods. When called, these methods send/receive a signal to/from a host-side proxy, which will trigger (R)DMA (such as `cudaMemcpy*` or `ibv_post_send`) or issue synchronization methods (such as `cudaStreamSynchronize` or `ibv_poll_cq`). Since the key functionalities are run by the proxy, `PortChannel` requires only a single GPU thread to call its methods. See all `PortChannel` methods from [here](./include/mscclpp/port_channel_device.hpp).
 
-On the other hand, `SmChannel` provides memory-mapping-based copy and synchronization methods. When called, these methods will directly use GPU threads to read/write from/to the remote GPU's memory space. Comparing against `ProxyChannel`, `SmChannel` is especially performant for low-latency scenarios, while it may need many GPU threads to call copying methods at the same time to achieve high copying bandwidth. See all `SmChannel` methods from [here](./include/mscclpp/sm_channel_device.hpp).
+On the other hand, `MemoryChannel` provides memory-mapping-based copy and synchronization methods. When called, these methods will directly use GPU threads to read/write from/to the remote GPU's memory space. Comparing against `PortChannel`, `MemoryChannel` is especially performant for low-latency scenarios, while it may need many GPU threads to call copying methods at the same time to achieve high copying bandwidth. See all `MemoryChannel` methods from [here](./include/mscclpp/memory_channel_device.hpp).
 
 ### Host-Side Communication Proxy
 
-MSCCL++ provides a default implementation of a host-side proxy for ProxyChannels, which is a background host thread that busy polls triggers from GPUs and conducts functionalities accordingly. For example, the following is a typical host-side code for MSCCL++.
+MSCCL++ provides a default implementation of a host-side proxy for PortChannels, which is a background host thread that busy polls triggers from GPUs and conducts functionalities accordingly. For example, the following is a typical host-side code for MSCCL++.
 
 ```cpp
 // Bootstrap: initialize control-plane connections between all ranks

apps/nccl/src/allgather.hpp

@@ -7,14 +7,14 @@
 #include <mscclpp/concurrency_device.hpp>
 #include <mscclpp/core.hpp>
 #include <mscclpp/gpu.hpp>
-#include <mscclpp/sm_channel.hpp>
-#include <mscclpp/sm_channel_device.hpp>
+#include <mscclpp/memory_channel.hpp>
+#include <mscclpp/memory_channel_device.hpp>
 
 #include "common.hpp"
 
 template <bool IsOutOfPlace>
 __global__ void __launch_bounds__(1024, 1)
-    allgather6(void* sendbuff, mscclpp::DeviceHandle<mscclpp::SmChannel>* smChannels, size_t channelOutOffset,
+    allgather6(void* sendbuff, mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryChannels, size_t channelOutOffset,
                size_t rank, [[maybe_unused]] size_t worldSize, size_t nRanksPerNode, size_t nelemsPerGPU) {
   const size_t tid = threadIdx.x + blockIdx.x * blockDim.x;
   const size_t lid = tid % WARP_SIZE;
@@ -24,11 +24,11 @@ __global__ void __launch_bounds__(1024, 1)
   const size_t nWarp = nThread / WARP_SIZE;
   const size_t nPeer = nRanksPerNode - 1;
   const size_t chanOffset = nPeer * blockIdx.x;
-  auto smChans = smChannels + chanOffset;
+  auto memChans = memoryChannels + chanOffset;
 
   if (threadIdx.x < nPeer) {
-    smChans[threadIdx.x].relaxedSignal();
-    smChans[threadIdx.x].wait();
+    memChans[threadIdx.x].relaxedSignal();
+    memChans[threadIdx.x].wait();
   }
   __syncthreads();
 
@@ -49,16 +49,16 @@ __global__ void __launch_bounds__(1024, 1)
     const size_t peerIdx = wid % nPeer;
     const size_t offset = bytesPerGPU * rank + (wid / nPeer) * unitBytesPerWarp;
     if constexpr (IsOutOfPlace) {
-      char* dst = reinterpret_cast<char*>(smChans[peerIdx].dst_);
-      char* src = reinterpret_cast<char*>(smChans[peerIdx].src_);
+      char* dst = reinterpret_cast<char*>(memChans[peerIdx].dst_);
+      char* src = reinterpret_cast<char*>(memChans[peerIdx].src_);
       char* buff = reinterpret_cast<char*>(sendbuff);
       const size_t offsetWithinRank = (wid / nPeer) * unitBytesPerWarp;
-      smChans[peerIdx].copy<16, false>(src + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
-                                       WARP_SIZE);
-      smChans[peerIdx].copy<16, false>(dst + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
-                                       WARP_SIZE);
+      memChans[peerIdx].copy<16, false>(src + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
+                                        WARP_SIZE);
+      memChans[peerIdx].copy<16, false>(dst + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
+                                        WARP_SIZE);
     } else {
-      smChans[peerIdx].put<16, false>(offset + channelOutOffset, unitBytesPerWarp, lid, WARP_SIZE);
+      memChans[peerIdx].put<16, false>(offset + channelOutOffset, unitBytesPerWarp, lid, WARP_SIZE);
     }
   }
 
@@ -67,16 +67,16 @@ __global__ void __launch_bounds__(1024, 1)
     const size_t peerIdx = gWid % nPeer;
     const size_t offset = bytesPerGPU * rank + (gWid / nPeer) * unitBytesPerWarp;
     if constexpr (IsOutOfPlace) {
-      char* dst = reinterpret_cast<char*>(smChans[peerIdx].dst_);
-      char* src = reinterpret_cast<char*>(smChans[peerIdx].src_);
+      char* dst = reinterpret_cast<char*>(memChans[peerIdx].dst_);
+      char* src = reinterpret_cast<char*>(memChans[peerIdx].src_);
       char* buff = reinterpret_cast<char*>(sendbuff);
       const size_t offsetWithinRank = (gWid / nPeer) * unitBytesPerWarp;
-      smChans[peerIdx].copy<16, false>(src + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
-                                       WARP_SIZE);
-      smChans[peerIdx].copy<16, false>(dst + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
-                                       WARP_SIZE);
+      memChans[peerIdx].copy<16, false>(src + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
+                                        WARP_SIZE);
+      memChans[peerIdx].copy<16, false>(dst + offset + channelOutOffset, buff + offsetWithinRank, unitBytesPerWarp, lid,
+                                        WARP_SIZE);
     } else {
-      smChans[peerIdx].put<16, false>(offset + channelOutOffset, unitBytesPerWarp, lid, WARP_SIZE);
+      memChans[peerIdx].put<16, false>(offset + channelOutOffset, unitBytesPerWarp, lid, WARP_SIZE);
     }
   }
 
@@ -90,30 +90,30 @@ __global__ void __launch_bounds__(1024, 1)
                                    : unitBytesPerWarp;
     if (remainBytes > 0) {
       if constexpr (IsOutOfPlace) {
-        char* dst = reinterpret_cast<char*>(smChans[peerIdx].dst_);
-        char* src = reinterpret_cast<char*>(smChans[peerIdx].src_);
+        char* dst = reinterpret_cast<char*>(memChans[peerIdx].dst_);
+        char* src = reinterpret_cast<char*>(memChans[peerIdx].src_);
         char* buff = reinterpret_cast<char*>(sendbuff);
-        smChans[peerIdx].copy<16, true>(src + offset + channelOutOffset, buff + offsetWithinRank, remainBytes, lid,
-                                        WARP_SIZE);
-        smChans[peerIdx].copy<16, true>(dst + offset + channelOutOffset, buff + offsetWithinRank, remainBytes, lid,
-                                        WARP_SIZE);
+        memChans[peerIdx].copy<16, true>(src + offset + channelOutOffset, buff + offsetWithinRank, remainBytes, lid,
+                                         WARP_SIZE);
+        memChans[peerIdx].copy<16, true>(dst + offset + channelOutOffset, buff + offsetWithinRank, remainBytes, lid,
+                                         WARP_SIZE);
       } else {
-        smChans[peerIdx].put<16, true>(offset + channelOutOffset, remainBytes, lid, WARP_SIZE);
+        memChans[peerIdx].put<16, true>(offset + channelOutOffset, remainBytes, lid, WARP_SIZE);
       }
     }
   }
 
   deviceSyncer.sync(gridDim.x);
 
   if (threadIdx.x < nPeer) {
-    smChans[threadIdx.x].relaxedSignal();
-    smChans[threadIdx.x].wait();
+    memChans[threadIdx.x].relaxedSignal();
+    memChans[threadIdx.x].wait();
   }
 }
 
 template <bool IsOutOfPlace, typename T>
 cudaError_t allgather(T* buff, [[maybe_unused]] T* scratch, [[maybe_unused]] T* resultBuff,
-                      mscclpp::DeviceHandle<mscclpp::SmChannel>* smChannels, size_t channelOutOffset, int rank,
+                      mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryChannels, size_t channelOutOffset, int rank,
                       int nRanksPerNode, int worldSize, size_t nelems, cudaStream_t stream) {
   int nBlocks = 28;
   if (nelems <= 4096) {
@@ -123,7 +123,7 @@ cudaError_t allgather(T* buff, [[maybe_unused]] T* scratch, [[maybe_unused]] T*
   } else if (nelems >= 2097152) {
     nBlocks = 35;
   }
-  allgather6<IsOutOfPlace><<<nBlocks, 1024, 0, stream>>>((void*)buff, smChannels, channelOutOffset, rank, worldSize,
+  allgather6<IsOutOfPlace><<<nBlocks, 1024, 0, stream>>>((void*)buff, memoryChannels, channelOutOffset, rank, worldSize,
                                                          nRanksPerNode, nelems * sizeof(T) / sizeof(int));
   return cudaGetLastError();
 }

apps/nccl/src/allreduce.hpp

@@ -8,9 +8,9 @@
 #include <mscclpp/core.hpp>
 #include <mscclpp/gpu.hpp>
 #include <mscclpp/gpu_data_types.hpp>
+#include <mscclpp/memory_channel.hpp>
+#include <mscclpp/memory_channel_device.hpp>
 #include <mscclpp/packet_device.hpp>
-#include <mscclpp/sm_channel.hpp>
-#include <mscclpp/sm_channel_device.hpp>
 
 #if defined(ENABLE_NPKIT)
 #include <mscclpp/npkit/npkit.hpp>
@@ -196,7 +196,7 @@ __forceinline__ __device__ void vectorSum(T* dst, T* src, size_t nElem) {
 
 template <typename T>
 __global__ void __launch_bounds__(32, 1)
-    allreduceAllToAll(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::SmChannel>* smChannels,
+    allreduceAllToAll(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryChannels,
                       size_t channelDataOffset, size_t channelScratchOffset, int rank, int nRanksPerNode, int worldSize,
                       size_t nelems, uint32_t flag) {
   // This version of allreduce only works for single nodes
@@ -213,10 +213,10 @@ __global__ void __launch_bounds__(32, 1)
   uint32_t* src = (uint32_t*)((char*)buff);
   uint32_t* dst = (uint32_t*)((char*)resultBuff);
 
-  __shared__ mscclpp::DeviceHandle<mscclpp::SmChannel> channels[NRANKS_PER_NODE - 1];
+  __shared__ mscclpp::DeviceHandle<mscclpp::MemoryChannel> channels[NRANKS_PER_NODE - 1];
   const int lid = tid % WARP_SIZE;
   if (lid < nPeers) {
-    channels[lid] = smChannels[lid];
+    channels[lid] = memoryChannels[lid];
   }
   __syncwarp();
 
@@ -240,7 +240,7 @@ __global__ void __launch_bounds__(32, 1)
 
 template <typename T>
 __global__ void __launch_bounds__(1024, 1)
-    allreduce7(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::SmChannel>* smChannels,
+    allreduce7(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryChannels,
                size_t channelDataOffset, size_t channelScratchOffset, int rank, int nRanksPerNode, int worldSize,
                size_t nelems, uint32_t flag
 #if defined(ENABLE_NPKIT)
@@ -304,10 +304,10 @@ __global__ void __launch_bounds__(1024, 1)
   uint2* dst = (uint2*)((char*)resultBuff + rank * nelemsPerRank * sizeof(int));
 
   // Put channels into shared memory, read channel info from global memory is unexpectable slow.
-  __shared__ mscclpp::DeviceHandle<mscclpp::SmChannel> channels[NRANKS_PER_NODE - 1];
+  __shared__ mscclpp::DeviceHandle<mscclpp::MemoryChannel> channels[NRANKS_PER_NODE - 1];
   const int lid = tid % WARP_SIZE;
   if (lid < nPeers) {
-    channels[lid] = smChannels[lid];
+    channels[lid] = memoryChannels[lid];
   }
   __syncwarp();
 
@@ -361,16 +361,16 @@ __global__ void __launch_bounds__(1024, 1)
 
 template <typename T>
 __global__ void __launch_bounds__(512, 1)
-    allreduce8(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::SmChannel>* smChannels,
-               mscclpp::DeviceHandle<mscclpp::SmChannel>* smOutChannels, size_t channelOutDataOffset,
+    allreduce8(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryChannels,
+               mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryOutChannels, size_t channelOutDataOffset,
                size_t channelScratchOffset, int rank, int nRanksPerNode, int worldSize, size_t nelems) {
   const int nPeer = nRanksPerNode - 1;
   const size_t chanOffset = nPeer * blockIdx.x;
   // assume (nelems * sizeof(T)) is divisible by (16 * worldSize)
   const size_t nInt4 = nelems * sizeof(T) / sizeof(int4);
   const size_t nInt4PerRank = nInt4 / worldSize;
-  auto smChans = smChannels + chanOffset;
-  auto smOutChans = smOutChannels + chanOffset;
+  auto memoryChans = memoryChannels + chanOffset;
+  auto memoryOutChans = memoryOutChannels + chanOffset;
 
   int4* buff4 = reinterpret_cast<int4*>(buff);
   int4* scratch4 = reinterpret_cast<int4*>((char*)scratch + channelScratchOffset);
@@ -396,12 +396,12 @@ __global__ void __launch_bounds__(512, 1)
   const size_t scratchChunkRankOffset = chunkSizePerRank * rank;
   const size_t scratchBaseOffsetInt4 = channelScratchOffset / sizeof(int4);
 
-  __shared__ mscclpp::DeviceHandle<mscclpp::SmChannel> channels[NRANKS_PER_NODE - 1];
-  __shared__ mscclpp::DeviceHandle<mscclpp::SmChannel> outChannels[NRANKS_PER_NODE - 1];
+  __shared__ mscclpp::DeviceHandle<mscclpp::MemoryChannel> channels[NRANKS_PER_NODE - 1];
+  __shared__ mscclpp::DeviceHandle<mscclpp::MemoryChannel> outChannels[NRANKS_PER_NODE - 1];
   const int lid = threadIdx.x % WARP_SIZE;
   if (lid < nPeer) {
-    channels[lid] = smChans[lid];
-    outChannels[lid] = smOutChans[lid];
+    channels[lid] = memoryChans[lid];
+    outChannels[lid] = memoryOutChans[lid];
   }
   __syncwarp();
 
@@ -496,18 +496,18 @@ __global__ void __launch_bounds__(512, 1)
 }
 
 template <typename T>
-cudaError_t allreduce(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::SmChannel>* smChannels,
-                      mscclpp::DeviceHandle<mscclpp::SmChannel>* smOutChannels, size_t channelInOffset,
+cudaError_t allreduce(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryChannels,
+                      mscclpp::DeviceHandle<mscclpp::MemoryChannel>* memoryOutChannels, size_t channelInOffset,
                       size_t channelOutOffset, size_t channelScratchOffset, int rank, int nRanksPerNode, int worldSize,
                       size_t nelems, cudaStream_t stream) {
   static uint32_t flag = 1;
 
   if (sizeof(T) * nelems < worldSize * sizeof(int)) {
     int nBlocks = 7;
     int nThreadsPerBlock = 32;
-    allreduceAllToAll<<<nBlocks, nThreadsPerBlock, 0, stream>>>(buff, scratch, resultBuff, smChannels, channelInOffset,
-                                                                channelScratchOffset, rank, nRanksPerNode, worldSize,
-                                                                nelems, flag++);
+    allreduceAllToAll<<<nBlocks, nThreadsPerBlock, 0, stream>>>(buff, scratch, resultBuff, memoryChannels,
+                                                                channelInOffset, channelScratchOffset, rank,
+                                                                nRanksPerNode, worldSize, nelems, flag++);
   } else if (sizeof(T) * nelems <= (1 << 20)) {
     int nBlocks = 28;
     int nThreadsPerBlock = 1024;
@@ -518,17 +518,17 @@ cudaError_t allreduce(T* buff, T* scratch, T* resultBuff, mscclpp::DeviceHandle<
 #if defined(ENABLE_NPKIT)
     size_t NpkitSharedMemSize = NPKIT_SHM_NUM_EVENTS * sizeof(NpKitEvent);
     allreduce7<<<nBlocks, nThreadsPerBlock, NpkitSharedMemSize, stream>>>(
-        buff, scratch, resultBuff, smChannels, channelInOffset, channelScratchOffset, rank, nRanksPerNode, worldSize,
-        nelems, flag++, NpKit::GetGpuEventCollectContexts(), NpKit::GetCpuTimestamp());
+        buff, scratch, resultBuff, memoryChannels, channelInOffset, channelScratchOffset, rank, nRanksPerNode,
+        worldSize, nelems, flag++, NpKit::GetGpuEventCollectContexts(), NpKit::GetCpuTimestamp());
 #else
-    allreduce7<<<nBlocks, nThreadsPerBlock, 0, stream>>>(buff, scratch, resultBuff, smChannels, channelInOffset,
+    allreduce7<<<nBlocks, nThreadsPerBlock, 0, stream>>>(buff, scratch, resultBuff, memoryChannels, channelInOffset,
                                                          channelScratchOffset, rank, nRanksPerNode, worldSize, nelems,
                                                          flag++);
 #endif
   } else {
     int nBlocks = 35;
     int nThreadsPerBlock = 512;
-    allreduce8<<<nBlocks, nThreadsPerBlock, 0, stream>>>(buff, scratch, resultBuff, smChannels, smOutChannels,
+    allreduce8<<<nBlocks, nThreadsPerBlock, 0, stream>>>(buff, scratch, resultBuff, memoryChannels, memoryOutChannels,
                                                          channelOutOffset, channelScratchOffset, rank, nRanksPerNode,
                                                          worldSize, nelems);
   }