作者|KIDGINBROOK
更新|潘丽晨
上次分析了NCCL对机器PCI系统进行拓扑分析的过程,产出的结果为xml格式,接下来,NCCL会根据这个xml进图的建立过程以便之后进行路径搜索。
ncclTopoGetSystem的最后会执行ncclTopoGetSystemFromXml将xml格式转成图格式。
ncclResult_t ncclTopoGetSystemFromXml(struct ncclXml* xml, struct ncclTopoSystem** topoSystem) {
NCCLCHECK(ncclCalloc(topoSystem, 1));
struct ncclXmlNode* topNode;
NCCLCHECK(xmlFindTag(xml, "system", &topNode));
for (int s=0; snSubs; s++) {
struct ncclXmlNode* node = topNode->subs[s];
if (strcmp(node->name, "cpu") == 0) NCCLCHECK(ncclTopoAddCpu(node, *topoSystem));
}
NCCLCHECK(ncclTopoAddNvLinks(topNode, *topoSystem, NULL));
NCCLCHECK(ncclTopoConnectCpus(*topoSystem));
NCCLCHECK(ncclTopoSortSystem(*topoSystem));
return ncclSuccess;
}
从xml中拿到根节点"system",然后遍历子节点中的"cpu",对每个cpu通过ncclTopoAddCpu进行建图,这里一个cpu其实就是一个numa。
ncclResult_t ncclTopoAddCpu(struct ncclXmlNode* xmlCpu, struct ncclTopoSystem* system) {
int numaId;
NCCLCHECK(xmlGetAttrInt(xmlCpu, "numaid", &numaId));
struct ncclTopoNode* cpu;
NCCLCHECK(ncclTopoCreateNode(system, &cpu, CPU, numaId));
const char* str;
NCCLCHECK(xmlGetAttr(xmlCpu, "affinity", &str));
if (str != NULL) {
NCCLCHECK(ncclStrToCpuset(str, &cpu->cpu.affinity));
}
NCCLCHECK(xmlGetAttrStr(xmlCpu, "arch", &str));
NCCLCHECK(kvConvertToInt(str, &cpu->cpu.arch, kvDictCpuArch));
if (cpu->cpu.arch == NCCL_TOPO_CPU_ARCH_X86) {
NCCLCHECK(xmlGetAttrStr(xmlCpu, "vendor", &str));
NCCLCHECK(kvConvertToInt(str, &cpu->cpu.vendor, kvDictCpuVendor));
if (cpu->cpu.vendor == NCCL_TOPO_CPU_VENDOR_INTEL) {
int familyId, modelId;
NCCLCHECK(xmlGetAttrInt(xmlCpu, "familyid", &familyId));
NCCLCHECK(xmlGetAttrInt(xmlCpu, "modelid", &modelId));
cpu->cpu.model = (familyId == 6 && modelId >= 0x55) ? NCCL_TOPO_CPU_TYPE_SKL : NCCL_TOPO_CPU_INTEL_BDW;
}
}
for (int s=0; snSubs; s++) {
struct ncclXmlNode* node = xmlCpu->subs[s];
if (strcmp(node->name, "pci") == 0) NCCLCHECK(ncclTopoAddPci(node, system, cpu));
if (strcmp(node->name, "nic") == 0) {
struct ncclTopoNode* nic = NULL;
NCCLCHECK(ncclTopoGetNode(system, &nic, NIC, 0));
if (nic == NULL) {
NCCLCHECK(ncclTopoCreateNode(system, &nic, NIC, 0));
NCCLCHECK(ncclTopoConnectNodes(cpu, nic, LINK_PCI, LOC_WIDTH));
NCCLCHECK(ncclTopoConnectNodes(nic, cpu, LINK_PCI, LOC_WIDTH));
}
NCCLCHECK(ncclTopoAddNic(node, system, nic));
}
}
return ncclSuccess;
}
接着创建一个cpu node,id为numaid,设置cpu的affinity,即该numa对应的核,设置cpu对应vendor等信息。
然后遍历cpu node的子节点,根据不同的类型执行不同的函数,如果是PCI节点,则执行ncclTopoAddPci。
ncclResult_t ncclTopoAddPci(struct ncclXmlNode* xmlPci, struct ncclTopoSystem* system, struct ncclTopoNode* parent) {
const char* str;
int type;
NCCLCHECK(xmlGetAttrStr(xmlPci, "class", &str));
NCCLCHECK(kvConvertToInt(str, &type, kvDictPciClass));
int64_t busId;
NCCLCHECK(xmlGetAttrStr(xmlPci, "busid", &str));
NCCLCHECK(busIdToInt64(str, &busId));
struct ncclTopoNode* node = NULL;
if (type == GPU) {
struct ncclXmlNode* xmlGpu;
NCCLCHECK(xmlGetSub(xmlPci, "gpu", &xmlGpu));
if (xmlGpu == NULL) return ncclSuccess;
int index;
NCCLCHECK(xmlGetAttrIndex(xmlGpu, "rank", &index));
if (index == -1) return ncclSuccess;
NCCLCHECK(ncclTopoCreateNode(system, &node, type, busId));
NCCLCHECK(ncclTopoAddGpu(xmlGpu, system, node));
}
if (type == NIC) {
struct ncclXmlNode* xmlNic;
NCCLCHECK(xmlGetSub(xmlPci, "nic", &xmlNic));
if (xmlNic == NULL) return ncclSuccess;
// Ignore sub device ID and merge multi-port NICs into one PCI device.
busId &= 0xfffffffffffffff0;
struct ncclTopoNode* nicNode = NULL;
NCCLCHECK(ncclTopoGetNode(system, &nicNode, type, busId));
if (nicNode == NULL) {
NCCLCHECK(ncclTopoCreateNode(system, &nicNode, type, busId));
node = nicNode; // Connect it to parent later on
}
NCCLCHECK(ncclTopoAddNic(xmlNic, system, nicNode));
} else if (type == PCI) {
NCCLCHECK(ncclTopoCreateNode(system, &node, type, busId));
for (int s=0; snSubs; s++) {
struct ncclXmlNode* xmlSubPci = xmlPci->subs[s];
NCCLCHECK(ncclTopoAddPci(xmlSubPci, system, node));
}
}
if (node) {
int width, speed;
NCCLCHECK(xmlGetAttrInt(xmlPci, "link_width", &width));
NCCLCHECK(xmlGetAttrStr(xmlPci, "link_speed", &str));
// Manage cases where speed was not indicated in /sys
if (width == 0) width = 16;
NCCLCHECK(kvConvertToInt(str, &speed, kvDictPciGen)); // Values in 100Mbps, per lane (we want GB/s in the end)
NCCLCHECK(ncclTopoConnectNodes(node, parent, LINK_PCI, width*speed/80.0));
NCCLCHECK(ncclTopoConnectNodes(parent, node, LINK_PCI, width*speed/80.0));
}
return ncclSuccess;
}
首先获取pci的type和busId, 然后判断type,如果是PCI,那么创建一个PCI node,递归执行ncclTopoAddPci,直到遇到NIC或者GPU xml节点。
如果遇到的是NIC,那么创建NIC节点,然后执行ncclTopoAddNic,这里会在xml nic下遍历xml net,对每个xml net创建net node,id为dev,然后设置speed,port,gdr等属性。
ncclResult_t ncclTopoAddNet(struct ncclXmlNode* xmlNet, struct ncclTopoSystem* system, struct ncclTopoNode* nic) {
int dev;
NCCLCHECK(xmlGetAttrInt(xmlNet, "dev", &dev));
struct ncclTopoNode* net;
NCCLCHECK(ncclTopoCreateNode(system, &net, NET, dev));
const char* str;
NCCLCHECK(xmlGetAttr(xmlNet, "guid", &str));
if (str) sscanf(str, "0x%lx", &net->net.asic);
else net->net.asic = dev;
ncclDebugNoWarn = NCCL_GRAPH;
int mbps;
if (xmlGetAttrInt(xmlNet, "speed", &mbps) != ncclSuccess) mbps = 0;
if (mbps <= 0) mbps = 10000; // Some NICs define speed = -1
net->net.width = mbps / 8000.0;
if (xmlGetAttrInt(xmlNet, "port", &net->net.port) != ncclSuccess) net->net.port = 0;
if (xmlGetAttrInt(xmlNet, "gdr", &net->net.gdrSupport) != ncclSuccess) net->net.gdrSupport = 0;
if (xmlGetAttrInt(xmlNet, "maxconn", &net->net.maxChannels) != ncclSuccess) net->net.maxChannels = MAXCHANNELS;
if (xmlGetAttrInt(xmlNet, "coll", &net->net.collSupport) != ncclSuccess) net->net.collSupport = 0;
ncclDebugNoWarn = 0;
NCCLCHECK(ncclTopoConnectNodes(nic, net, LINK_NET, net->net.width));
NCCLCHECK(ncclTopoConnectNodes(net, nic, LINK_NET, net->net.width));
return ncclSuccess;
}
ncclResult_t ncclTopoAddNic(struct ncclXmlNode* xmlNic, struct ncclTopoSystem* system, struct ncclTopoNode* nic) {
for (int s=0; snSubs; s++) {
struct ncclXmlNode* xmlNet = xmlNic->subs[s];
if (strcmp(xmlNet->name, "net") != 0) continue;
int index;
NCCLCHECK(xmlGetAttrIndex(xmlNet, "dev", &index));
if (index == -1) continue;
NCCLCHECK(ncclTopoAddNet(xmlNet, system, nic));
}
return ncclSuccess;
}
然后通过建立net node到nic node的正反向边,设置边的类型,边上累计带宽,并且当前节点的边按照带宽从大到小排序。
ncclResult_t ncclTopoConnectNodes(struct ncclTopoNode* node, struct ncclTopoNode* remNode, int type, float width) {
// Aggregate links into higher width for NVLink
struct ncclTopoLink* link;
for (link = node->links; link->remNode; link++) {
if (link->remNode == remNode && link->type == type) break;
}
if (link->remNode == NULL) node->nlinks++;
link->type = type;
link->remNode = remNode;
link->width += width;
// Sort links in BW descending order
struct ncclTopoLink linkSave;
memcpy(&linkSave, link, sizeof(struct ncclTopoLink));
while (link != node->links) {
if ((link-1)->width >= linkSave.width) break;
memcpy(link, link-1, sizeof(struct ncclTopoLink));
link--;
}
memcpy(link, &linkSave, sizeof(struct ncclTopoLink));
return ncclSuccess;
}
到这里就添加完成了NIC,回到ncclTopoAddPci里,如果是gpu的话则创建gpu node,然后设置gpu node的rank,dev,gdr等属性。最后通过ncclTopoConnectNodes建立当前节点到子节点的双向边。
到这里就完成了每个numa节点下的建图,然后开始添加nvlink和QPI以连接,先看下nvlink。
ncclResult_t ncclTopoAddNvLinks(struct ncclXmlNode* node, struct ncclTopoSystem* system, const char* parentBusId) {
if (strcmp(node->name, "nvlink") == 0) {
struct ncclTopoNode* gpu = NULL;
int64_t pBusId;
NCCLCHECK(busIdToInt64(parentBusId, &pBusId));
NCCLCHECK(ncclTopoGetNode(system, &gpu, GPU, pBusId));
if (gpu == NULL) {
WARN("Add NVLink error : could not find GPU %lx\n", pBusId);
return ncclInternalError;
}
int count;
NCCLCHECK(xmlGetAttrInt(node, "count", &count));
const char* targetClass;
NCCLCHECK(xmlGetAttrStr(node, "tclass", &targetClass));
int targetType;
NCCLCHECK(kvConvertToInt(targetClass, &targetType, kvDictPciClass));
struct ncclTopoNode* remote = NULL;
if (targetType == GPU) {
// NVL P2P connection to another GPU
const char* target;
NCCLCHECK(xmlGetAttrStr(node, "target", &target));
int64_t busId;
NCCLCHECK(busIdToInt64(target, &busId));
NCCLCHECK(ncclTopoGetNode(system, &remote, GPU, busId));
} else if (targetType == CPU) {
// NVL connection to the local CPU
NCCLCHECK(findLocalCpu(gpu, &remote));
} else {
if (system->nodes[NVS].count == 0) {
NCCLCHECK(ncclTopoCreateNode(system, &remote, NVS, 0));
} else {
remote = system->nodes[NVS].nodes;
}
}
if (remote) {
int nvlSpeed = gpu->gpu.cudaCompCap == 60 ? PASCAL_NVLINK_WIDTH : VOLTA_NVLINK_WIDTH;
NCCLCHECK(ncclTopoConnectNodes(gpu, remote, LINK_NVL, count*nvlSpeed));
if (remote->type != GPU) {
NCCLCHECK(ncclTopoConnectNodes(remote, gpu, LINK_NVL, count*nvlSpeed));
}
}
} else {
const char* busId;
NCCLCHECK(xmlGetAttr(node, "busid", &busId));
for (int s=0; snSubs; s++) {
NCCLCHECK(ncclTopoAddNvLinks(node->subs[s], system, busId ? busId : parentBusId));
}
}
return ncclSuccess;
}
从根节点递归遍历下去,直到遇到nvlink xml节点,然后拿到nvlink的父节点,即gpu节点,然后通过tclass获取对端PCI设备类型,如果是gpu或者cpu,直接返回对端node,如果是nvswitch,那就先创建nvswitch节点,然后创建当前gpu节点和对端的双向边。然后通过ncclTopoConnectCpus将cpu两两连接。
最后为了方便后续搜索channel,通过ncclTopoSort递归将每个PCI节点的边按照nvlink,向下的PCI连接,向上的PCI连接,QPI的顺序进行排序,因为建边的过程中已经按照带宽排序过,所以nvlink一定在最前边,QPI一定在最后,因此只需要对中间的PCI排序即可。
static ncclResult_t ncclTopoSort(struct ncclTopoNode* node, struct ncclTopoNode* upNode) {
// Shift all links to have upLink as last link
if (upNode) {
int l=0;
while (node->links[l].remNode != upNode) l++;
struct ncclTopoLink upLink;
memcpy(&upLink, node->links+l, sizeof(struct ncclTopoLink));
while (node->links[l+1].remNode) {
memcpy(node->links+l, node->links+l+1, sizeof(struct ncclTopoLink));
l++;
}
memcpy(node->links+l, &upLink, sizeof(struct ncclTopoLink));
}
// Recursively sort the PCI tree
for (int l=0; lnlinks; l++) {
struct ncclTopoLink* link = node->links+l;
if (link->type == LINK_PCI && link->remNode != upNode) NCCLCHECK(ncclTopoSort(link->remNode, node));
}
return ncclSuccess;
}
到这里就完成了整个的建图过程。总结下,由于拓扑分析产出的xml不便于进行后续的路径搜索,所以本节基于xml对PCI系统进行了建图。
其他人都在看
关于语言大模型的八大论断
揭示GPT Tokenizer的工作原理
语言大模型100K上下文窗口的秘诀
GPT总设计师:大型语言模型的未来
NCCL源码解析③:机器内拓扑分析
OneEmbedding:单卡训练TB级推荐模型不是梦
GLM训练加速:性能最高提升3倍,显存节省1/3
试用OneFlow: github.com/Oneflow-Inc/oneflow/