NCCL源码解析③：机器内拓扑分析

作者｜KIDGINBROOK
更新｜潘丽晨

上节介绍所有节点执行了bootstrap网络连接的建立，接下来介绍下拓扑分析。

由于GPU机器架构是多种多样的，一台机器上可能有多个网卡，多个GPU卡，卡间连接也各不相同，因此需要对机器内设备连接拓扑进行分析，以使性能在各种拓扑结构下都尽可能好。

接着上回继续看initTransportsRank。

static ncclResult_t initTransportsRank(struct ncclComm* comm, ncclUniqueId* commId) {
  // We use 3 AllGathers
  // 1. { peerInfo, comm }
  // 2. ConnectTransport[nranks], ConnectValue[nranks]
  // 3. { nThreads, nrings, compCap, prev[MAXCHANNELS], next[MAXCHANNELS] }
 
  int rank = comm->rank;
  int nranks = comm->nRanks;
  uint64_t commHash = getHash(commId->internal, NCCL_UNIQUE_ID_BYTES);
  TRACE(NCCL_INIT, "comm %p, commHash %lx, rank %d nranks %d - BEGIN", comm, commHash, rank, nranks);
  NCCLCHECK(bootstrapInit(commId, rank, nranks, &comm->bootstrap));
 
  // AllGather1 - begin
  struct {
    struct ncclPeerInfo peerInfo;
    struct ncclComm* comm;
  } *allGather1Data;
 
  NCCLCHECK(ncclCalloc(&allGather1Data, nranks));
  allGather1Data[rank].comm = comm;
  struct ncclPeerInfo* myInfo = &allGather1Data[rank].peerInfo;
  NCCLCHECK(fillInfo(comm, myInfo, commHash));
  ...
}

创建nrank个allGather1Data，然后通过fillInfo 填充当前rank的peerInfo，ncclPeerInfo是rank的一些基本信息，比如rank号，在哪个机器的哪个进程等。

struct ncclPeerInfo {
  int rank;
  int cudaDev;
  int gdrSupport;
  uint64_t hostHash;
  uint64_t pidHash;
  dev_t shmDev;
  int64_t busId;
};
 
static ncclResult_t fillInfo(struct ncclComm* comm, struct ncclPeerInfo* info, uint64_t commHash) {
  info->rank = comm->rank;
  CUDACHECK(cudaGetDevice(&info->cudaDev));
  info->hostHash=getHostHash()+commHash;
  info->pidHash=getPidHash()+commHash;
 
  // Get the device MAJOR:MINOR of /dev/shm so we can use that
  // information to decide whether we can use SHM for inter-process
  // communication in a container environment
  struct stat statbuf;
  SYSCHECK(stat("/dev/shm", &statbuf), "stat");
  info->shmDev = statbuf.st_dev;
 
  info->busId = comm->busId;
 
  NCCLCHECK(ncclGpuGdrSupport(&info->gdrSupport));
  return ncclSuccess;
}

获取当前卡的rank，PCIe busId，/dev/shm的设备号，填充到ncclPeerInfo，然后通过ncclGpuGdrSupport查看是否支持gdr，rdma在通信前需要注册一段内存，使得网卡知道虚拟地址和物理地址的映射，但是如果每次通信都需要将data从显存拷贝到内存再通信的话效率就比较低。

而IB提供了peer memory的接口，使得ib网卡可以访问其他PCIe空间，nv基于peer memory实现了自己的驱动，使得rdma可以直接注册显存，这样通信就可以避免host和device的内存拷贝，IB可以直接dma显存，即gdr。

static ncclResult_t ncclGpuGdrSupport(int* gdrSupport) {
  int netDevs;
  NCCLCHECK(ncclNetDevices(&netDevs));
  *gdrSupport = 0;
  for (int dev=0; devgetProperties(dev, &props));
    if ((props.ptrSupport & NCCL_PTR_CUDA) == 0) continue;
 
    // Allocate memory on the GPU and try to register it on the NIC.
    void *lComm = NULL, *sComm = NULL, *rComm = NULL;
    ncclNetHandle_t handle;
    void* gpuPtr = NULL;
    void* mHandle = NULL;
    NCCLCHECK(ncclNetListen(dev, &handle, &lComm));
    NCCLCHECK(ncclNetConnect(dev, &handle, &sComm));
    NCCLCHECK(ncclNetAccept(lComm, &rComm));
    CUDACHECK(cudaMalloc(&gpuPtr, GPU_BUF_SIZE));
    ncclDebugNoWarn = NCCL_NET;
    if (ncclNetRegMr(sComm, gpuPtr, GPU_BUF_SIZE, NCCL_PTR_CUDA, &mHandle) == ncclSuccess) {
      NCCLCHECK(ncclNetDeregMr(sComm, mHandle));
      NCCLCHECK(ncclNetRegMr(rComm, gpuPtr, GPU_BUF_SIZE, NCCL_PTR_CUDA, &mHandle));
      NCCLCHECK(ncclNetDeregMr(rComm, mHandle));
      *gdrSupport = 1;
    }
    ncclDebugNoWarn = 0;
    CUDACHECK(cudaFree(gpuPtr));
    NCCLCHECK(ncclNetCloseRecv(rComm));
    NCCLCHECK(ncclNetCloseSend(sComm));
    NCCLCHECK(ncclNetCloseListen(lComm));
    break;
  }
  return ncclSuccess;
}

这里会遍历每一个网卡，获取网卡的信息，由第一节可以知道这里的ncclNet就是ncclNetIb。

ncclResult_t ncclIbGdrSupport(int ibDev) {
  static int moduleLoaded = -1; 
  if (moduleLoaded == -1) {
    moduleLoaded = (access("/sys/kernel/mm/memory_peers/nv_mem/version", F_OK) == -1) ? 0 : 1;
  }
  if (moduleLoaded == 0) return ncclSystemError;
  return ncclSuccess;
}
 
ncclResult_t ncclIbGetProperties(int dev, ncclNetProperties_t* props) {
  props->name = ncclIbDevs[dev].devName;
  props->pciPath = ncclIbDevs[dev].pciPath;
  props->guid = ncclIbDevs[dev].guid;
  props->ptrSupport = NCCL_PTR_HOST;
  if (ncclIbGdrSupport(dev) != ncclSuccess) {
    INFO(NCCL_NET,"NET/IB : GPU Direct RDMA Disabled for HCA %d '%s' (no module)", dev, ncclIbDevs[dev].devName);
  } else {
    props->ptrSupport |= NCCL_PTR_CUDA;
  }
  props->speed = ncclIbDevs[dev].speed;
  props->port = ncclIbDevs[dev].port + ncclIbDevs[dev].realPort;
  props->maxComms = ncclIbDevs[dev].maxQp;
  return ncclSuccess;
}

这里主要是获取网卡名，PCIe路径，guid等信息，然后查看是否有/sys/kernel/mm/memory_peers/nv_mem/version判断是否安装了nv_peermem，即nv的驱动，如果安装了的话则设置props->ptrSupport |= NCCL_PTR_CUDA，表示可以注册显存。

然后尝试注册显存，如果可以注册则设置gdrSupport为1，这里其实会创建rdma连接，这个在后边会单独介绍，本次先略过

static ncclResult_t initTransportsRank(struct ncclComm* comm, ncclUniqueId* commId) {
  ...
  NCCLCHECK(bootstrapAllGather(comm->bootstrap, allGather1Data, sizeof(*allGather1Data)));
 
  NCCLCHECK(ncclCalloc(&comm->peerInfo, nranks+1)); // Extra rank to represent CollNet root
  for (int i = 0; i peerInfo+i, &allGather1Data[i].peerInfo, sizeof(struct ncclPeerInfo));
    if ((i != rank) && (comm->peerInfo[i].hostHash == myInfo->hostHash) && (comm->peerInfo[i].busId == myInfo->busId)) {
      WARN("Duplicate GPU detected : rank %d and rank %d both on CUDA device %x", rank, i, myInfo->busId);
      return ncclInvalidUsage;
    }
  }
  // AllGather1 data is used again below
  // AllGather1 - end
 
  // Topo detection / System graph creation
  NCCLCHECK(ncclTopoGetSystem(comm, &comm->topo));
  ...
}

然后bootstrapAllGather广播allGather1Data，将获取到的其他节点peerinfo拷贝到comm里。

在看具体拓扑分析流程之前先简单了解一下PCIe的一些概念，一个简单的PCIe系统示例如下。

每个CPU都有自己的root complex，后简称为RC，RC会帮助cpu和其他部分通信，比如和内存，和PCIe系统，当cpu发送过来一个物理地址之后，如果这个地址是在PCIe空间，会被RC转换成PCIe请求进行通信。

switch的作用是扩展PCIe端口，下边可以连接设备或者其他switch，上游来的请求被被他转发，PCIe设备可以连在RC，也可以连在swtich，一个switch的内部如下所示

内部有一个PCIe总线 ，然后通过多个Bridge扩展出多个端口，其中上边的那个称为上游端口，其他的叫做下游端口。

前文有提到NCCL中很常用的一个变量名叫busId，比如gpu和ib网卡，注意区分NCCL里的busId并不是指的总线号，指的其实是定位一个PCIe设备用到的id，即BDF(bus + device + function)，一个bus上有多个设备，一个设备有多个功能，因此通过BDF就可以定位一个设备，在机器启动完成PCIe的配置之后会将相关信息通过sysfs提供给用户，NCCL就是通过sysfs来完成拓扑检测的。

然后看下执行的ncclTopoGetSystem，这个函数就是本节的重点，会将当前rank的PCI树建立起来，分为两个步骤，先使用xml表示整个PCI树结构，然后基于xml转成ncclTopoNode，其中xml定义如下，一个ncclXmlNode表示了PCI树的一个节点。

struct ncclXmlNode {
  char name[MAX_STR_LEN];
  struct {
    char key[MAX_STR_LEN];
    char value[MAX_STR_LEN];
  } attrs[MAX_ATTR_COUNT+1]; // Need an extra one to consume extra params
  int nAttrs;
  int type;
  struct ncclXmlNode* parent;
  struct ncclXmlNode* subs[MAX_SUBS];
  int nSubs;
};
 
struct ncclXml {
  struct ncclXmlNode nodes[MAX_NODES];
  int maxIndex;
};

ncclXmlNode表示一个节点，记录了父节点和所有子节点，节点有name和attr，通过xmlSetAttr进行设置属性。
ncclXml中预分配了所有的node，maxIndex表示分配到了哪里，然后简单介绍下几个xml相关的api。

static ncclResult_t xmlAddNode(struct ncclXml* xml, struct ncclXmlNode* parent, const char* subName, struct ncclXmlNode** sub);

xmlAddNode进行node的分配，表示在xml里新申请一个节点sub，sub的name设置为subName，父节点为parent。

static ncclResult_t xmlFindTagKv(struct ncclXml* xml, const char* tagName, struct ncclXmlNode** node, const char* attrName, const char* attrValue)

xmlFindTagKv会遍历xml已分配的节点，找到节点名为tagName的节点n，然后判断节点n[“attrName”]是否等于attrValue，如果相等，则设置node为n。

static ncclResult_t xmlGetAttrIndex(struct ncclXmlNode* node, const char* attrName, int* index)

xmlGetAttrIndex会查看attrName是node的第几个属性。

然后开始看拓扑分析的过程。

ncclResult_t ncclTopoGetSystem(struct ncclComm* comm, struct ncclTopoSystem** system) {
  struct ncclXml* xml;
  NCCLCHECK(ncclCalloc(&xml, 1));
  char* xmlTopoFile = getenv("NCCL_TOPO_FILE");
  if (xmlTopoFile) {
    INFO(NCCL_ENV, "NCCL_TOPO_FILE set by environment to %s", xmlTopoFile);
    NCCLCHECK(ncclTopoGetXmlFromFile(xmlTopoFile, xml));
  }
  if (xml->maxIndex == 0) {
    // Create top tag
    struct ncclXmlNode* top;
    NCCLCHECK(xmlAddNode(xml, NULL, "system", &top));
    NCCLCHECK(xmlSetAttrInt(top, "version", NCCL_TOPO_XML_VERSION));
  }
 
  // Auto-detect GPUs if needed
  for (int r=0; rnRanks; r++) {
    if (comm->peerInfo[r].hostHash == comm->peerInfo[comm->rank].hostHash) {
      char busId[NVML_DEVICE_PCI_BUS_ID_BUFFER_SIZE];
      NCCLCHECK(int64ToBusId(comm->peerInfo[r].busId, busId));
      struct ncclXmlNode* node;
      NCCLCHECK(ncclTopoFillGpu(xml, busId, &node));
      if (node == NULL) continue;
      NCCLCHECK(xmlSetAttrInt(node, "rank", r));
      NCCLCHECK(xmlInitAttrInt(node, "gdr", comm->peerInfo[r].gdrSupport));
    }   
  }
  ...
}

首先通过xmlAddNode创建根节点”system”（后续使用双引号表示xml树节点），并设置根节点属性”system” [“version”] = NCCL_TOPO_XML_VERSION，然后遍历每个rank的hosthash，如果相等的话说明在同一个机器，然后执行ncclTopoFillGpu，将gpu加入到xml树。

ncclResult_t ncclTopoFillGpu(struct ncclXml* xml, const char* busId, struct ncclXmlNode** gpuNode) {
  struct ncclXmlNode* node;
  NCCLCHECK(ncclTopoGetPciNode(xml, busId, &node));
  NCCLCHECK(ncclTopoGetXmlFromSys(node, xml));
  ...
}

ncclResult_t ncclTopoGetPciNode(struct ncclXml* xml, const char* busId, struct ncclXmlNode** pciNode) {
  NCCLCHECK(xmlFindTagKv(xml, "pci", pciNode, "busid", busId));
  if (*pciNode == NULL) {
    NCCLCHECK(xmlAddNode(xml, NULL, "pci", pciNode));
  }
  NCCLCHECK(xmlSetAttr(*pciNode, "busid", busId));
  return ncclSuccess;
}

通过ncclTopoGetPciNode获取xml中的有没有创建当前卡的xml node，此时没有，所以就新建一个xml node叫做”pci”，表示当前gpu卡，设置”pci”[“busid”]=busd。

然后执行ncclTopoGetXmlFromSys，这个函数主要逻辑就是在sysfs中获取gpu节点到cpu的路径，通过这个路径转成xml树，并读取该路径下相关属性设置到xml里。

ncclResult_t ncclTopoGetXmlFromSys(struct ncclXmlNode* pciNode, struct ncclXml* xml) {
  // Fill info, then parent
  const char* busId;
  NCCLCHECK(xmlGetAttr(pciNode, "busid", &busId));
  char* path = NULL;
  int index;
  NCCLCHECK(xmlGetAttrIndex(pciNode, "class", &index));
  if (index == -1) {
    if (path == NULL) NCCLCHECK(getPciPath(busId, &path));
    NCCLCHECK(ncclTopoSetAttrFromSys(pciNode, path, "class", "class"));
  }
  NCCLCHECK(xmlGetAttrIndex(pciNode, "link_speed", &index));
  if (index == -1) {
    if (path == NULL) NCCLCHECK(getPciPath(busId, &path));
    char deviceSpeedStr[MAX_STR_LEN];
    float deviceSpeed;
    NCCLCHECK(ncclTopoGetStrFromSys(path, "max_link_speed", deviceSpeedStr));
    sscanf(deviceSpeedStr, "%f GT/s", &deviceSpeed);
    char portSpeedStr[MAX_STR_LEN];
    float portSpeed;
    NCCLCHECK(ncclTopoGetStrFromSys(path, "../max_link_speed", portSpeedStr));
    sscanf(portSpeedStr, "%f GT/s", &portSpeed);
    NCCLCHECK(xmlSetAttr(pciNode, "link_speed", portSpeed 

首先设置pciNode的各种属性，通过getPciPath获取busId对应的sysfs路径path，其实这个路径就是PCI树中根到叶结点的路径。

static ncclResult_t getPciPath(const char* busId, char** path) {
  char busPath[] = "/sys/class/pci_bus/0000:00/../../0000:00:00.0";
  memcpylower(busPath+sizeof("/sys/class/pci_bus/")-1, busId, BUSID_REDUCED_SIZE-1);
  memcpylower(busPath+sizeof("/sys/class/pci_bus/0000:00/../../")-1, busId, BUSID_SIZE-1);
  *path = realpath(busPath, NULL);
  if (*path == NULL) {
    WARN("Could not find real path of %s", busPath);
    return ncclSystemError;
  }
  return ncclSuccess;
}

举个例子比如path是 /sys/devices/pci0000:10/0000:10:00.0/0000:11:00.0/0000:12:00.0/0000:13:00.0/0000
:14:00.0/0000:15:00.0/0000:16:00.0/0000:17:00.0，其中GPU的busId是0000:17:00.0，那么这个path对应下图，注意，下图略去了15:00.0对应的switch。

然后读取path下的属性，获取class（PCI设备类型），link_speed，link_width等设置到xml pciNode中，ncclTopoGetStrFromSys其实就是读取path下的内核文件保存到strValue。

ncclResult_t ncclTopoGetStrFromSys(const char* path, const char* fileName, char* strValue) {
  char filePath[PATH_MAX];
  sprintf(filePath, "%s/%s", path, fileName);
  int offset = 0;
  FILE* file;
  if ((file = fopen(filePath, "r")) != NULL) {
    while (feof(file) == 0 && ferror(file) == 0 && offset 

ncclResult_t ncclTopoGetXmlFromSys(struct ncclXmlNode* pciNode, struct ncclXml* xml) {
  // Fill info, then parent
  ...
  struct ncclXmlNode* parent = pciNode->parent;
  if (parent == NULL) {
    if (path == NULL) NCCLCHECK(getPciPath(busId, &path));
 
    // Save that for later in case next step is a CPU
    char numaIdStr[MAX_STR_LEN];
    NCCLCHECK(ncclTopoGetStrFromSys(path, "numa_node", numaIdStr));
 
    // Go up one level in the PCI tree. Rewind two "/" and follow the upper PCI
    // switch, or stop if we reach a CPU root complex.
    int slashCount = 0;
    int parentOffset;
    for (parentOffset = strlen(path)-1; parentOffset>0; parentOffset--) {
      if (path[parentOffset] == '/') {
        slashCount++;
        path[parentOffset] = '';
        int start = parentOffset - 1;
        while (start>0 && path[start] != '/') start--;
        // Check whether the parent path looks like "BBBB:BB:DD.F" or not.
        if (checkBDFFormat(path+start+1) == 0) {
          // This a CPU root complex. Create a CPU tag and stop there.
          struct ncclXmlNode* topNode;
          NCCLCHECK(xmlFindTag(xml, "system", &topNode));
          NCCLCHECK(xmlGetSubKv(topNode, "cpu", &parent, "numaid", numaIdStr));
          if (parent == NULL) {
            NCCLCHECK(xmlAddNode(xml, topNode, "cpu", &parent));
            NCCLCHECK(xmlSetAttr(parent, "numaid", numaIdStr));
          }
        } else if (slashCount == 2) {
          // Continue on the upper PCI switch
          for (int i = strlen(path)-1; i>0; i--) {
            if (path[i] == '/') {
              NCCLCHECK(xmlFindTagKv(xml, "pci", &parent, "busid", path+i+1));
              if (parent == NULL) {
                NCCLCHECK(xmlAddNode(xml, NULL, "pci", &parent));
                NCCLCHECK(xmlSetAttr(parent, "busid", path+i+1));
              }
              break;
            }
          }
        }
      }
      if (parent) break;
    }
    pciNode->parent = parent;
    parent->subs[parent->nSubs++] = pciNode;
  }
  if (strcmp(parent->name, "pci") == 0) {
    NCCLCHECK(ncclTopoGetXmlFromSys(parent, xml));
  } else if (strcmp(parent->name, "cpu") == 0) {
    NCCLCHECK(ncclTopoGetXmlFromCpu(parent, xml));
  }
  free(path);
  return ncclSuccess;
}

然后从pciNode开始往上跳，因为一个switch的上游端口和下游端口分别对应了一个bridge，NCCL使用上游端口bridge的busid表示这个switch，因此这里要向上跳两次再建立一个xml node表示这个switch，往上找到一个PCI设备就将slashCount加一

当slashCount==2就找到了一个switch上游端口，这个时候创建一个新的xml pci节点parent表示当前switch，然后将当前节点pciNode链接到parent，此时parent仍然是xml pci节点。

因此，继续递归执行ncclTopoGetXmlFromSys，直到遇到RC，此时给”system”创建一个子节点”cpu”，停止递归，然后执行ncclTopoGetXmlFromCpu，设置”cpu”的各种属性，比如arch（比如x86还是arm），affinity（该cpu的numa都有哪些cpu core），numaid等。

到这里ncclTopoGetXmlFromSys就执行结束了，接着看ncclTopoFillGpu。

ncclResult_t ncclTopoFillGpu(struct ncclXml* xml, const char* busId, struct ncclXmlNode** gpuNode) {
  ...
  NCCLCHECK(wrapNvmlSymbols());
  NCCLCHECK(wrapNvmlInit());
  nvmlDevice_t nvmlDev;
  if (wrapNvmlDeviceGetHandleByPciBusId(busId, &nvmlDev) != ncclSuccess) nvmlDev = NULL;
  NCCLCHECK(ncclTopoGetXmlFromGpu(node, nvmlDev, xml, gpuNode));
  return ncclSuccess;
}

然后通过wrapNvmlSymbols加载动态库libnvidia-ml.so.1，用来获取gpu的相关信息。

ncclResult_t ncclTopoGetXmlFromGpu(struct ncclXmlNode* pciNode, nvmlDevice_t nvmlDev, struct ncclXml* xml, struct ncclXmlNode** gpuNodeRet) {
  struct ncclXmlNode* gpuNode = NULL;
  NCCLCHECK(xmlGetSub(pciNode, "gpu", &gpuNode));
  if (gpuNode == NULL) NCCLCHECK(xmlAddNode(xml, pciNode, "gpu", &gpuNode));
 
  int index = -1;
 
  int dev = -1;
  NCCLCHECK(xmlGetAttrIndex(gpuNode, "dev", &index));
  if (index == -1) {
    if (nvmlDev == NULL) {
      WARN("No NVML, trying to use CUDA instead");
      const char* busId;
      NCCLCHECK(xmlGetAttr(pciNode, "busid", &busId));
      if (busId == NULL || cudaDeviceGetByPCIBusId(&dev, busId) != cudaSuccess) dev = -1;
    } else {
      NCCLCHECK(wrapNvmlDeviceGetIndex(nvmlDev, (unsigned int*)&dev));
    }
    NCCLCHECK(xmlSetAttrInt(gpuNode, "dev", dev));
  }
  NCCLCHECK(xmlGetAttrInt(gpuNode, "dev", &dev));
  if (dev == -1) { *gpuNodeRet = NULL; return ncclSuccess; }
 
  NCCLCHECK(xmlGetAttrIndex(gpuNode, "sm", &index));
  if (index == -1) {
    int cudaMajor, cudaMinor;
    if (nvmlDev == NULL) {
      cudaDeviceProp devProp;
      CUDACHECK(cudaGetDeviceProperties(&devProp, dev));
      cudaMajor = devProp.major; cudaMinor = devProp.minor;
    } else {
      NCCLCHECK(wrapNvmlDeviceGetCudaComputeCapability(nvmlDev, &cudaMajor, &cudaMinor));
    }
    NCCLCHECK(xmlSetAttrInt(gpuNode, "sm", cudaMajor*10+cudaMinor));
  }
  int sm;
  NCCLCHECK(xmlGetAttrInt(gpuNode, "sm", &sm));
 
  struct ncclXmlNode* nvlNode = NULL;
  NCCLCHECK(xmlGetSub(pciNode, "nvlink", &nvlNode));
  if (nvlNode == NULL) {
    // NVML NVLink detection
    int maxNvLinks = (sm  0 && nvmlDev == NULL) {
      WARN("No NVML device handle. Skipping nvlink detection.n");
      maxNvLinks = 0;
    }
 
    for (int l=0; lnSubs; s++) {
    struct ncclXmlNode* sub = gpuNode->subs[s];
    if (strcmp(sub->name, "nvlink") != 0) continue;
    int index;
    NCCLCHECK(xmlGetAttrIndex(sub, "tclass", &index));
    if (index == -1) {
      const char* busId;
      NCCLCHECK(xmlGetAttr(sub, "target", &busId));
      if (strcmp(busId, "fffffff:ffff:ff") == 0) {
        // Remote NVLink device is not visible inside this VM. Assume NVSwitch.
        NCCLCHECK(xmlSetAttr(sub, "tclass", "0x068000"));
      } else {
        char* path;
        NCCLCHECK(getPciPath(busId, &path));
        NCCLCHECK(ncclTopoSetAttrFromSys(sub, path, "class", "tclass"));
      }
    }
  }
  *gpuNodeRet = gpuNode;
  return ncclSuccess;
}

首先在xml gpu节点”pci”下创建节点”gpu”，然后设置”gpu”节点的属性，比如dev，计算能力sm，然后开始查询nvlink相关信息，遍历所有可能的nvlink，通过nvmlDeviceGetNvLinkCapability查询nvlink信息。

如果这个nvlink被启用，那么在”gpu”节点下新建一个”nvlink”节点，设置”target”属性表示nvlink对端的PCIe busId，将”target”相同的”nvlink”节点表示为一个，用”count”表示起止点之间有多少条nvlink，然后设置属性”tclass”表示”target”是什么类型的PCI设备。

到这里ncclTopoFillGpu就执行结束了，此时xml如下所示，图里只展示了一张网卡的情况，其中”gpu”和他的父节点其实都是指的同一个gpu。

然后回到ncclTopoGetSystem，会设置”gpu”的rank和gdr属性。

然后是对于所有的网卡，类似上述gpu的过程，通过ncclTopoGetXmlFromSys建立xml树，如下所示，只展示一张网卡的情况，其中”net”，”nic”和”nic”的父节点都表示同一张网卡。

总结一下，本节主要介绍了NCCL拓扑分析的过程，通过sysfs将gpu和网卡对应的pci树结构建立出来了xml树。

（原文：
https://blog.csdn.net/KIDGIN7439/article/details/126990961）

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