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profile effective CPU expert bandwidth

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This commit is contained in:
ZacharyZcR
2026-07-18 05:34:41 +08:00
parent c3a90eca36
commit 570d738ed5
3 changed files with 22 additions and 10 deletions
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c/glm.c
+17 -6
View File
@@ -203,6 +203,7 @@ typedef struct {
double route_kl_sum; uint64_t route_kl_n; /* mean KL(true||chosen) on gate mass */
double t_ewait, t_emm, t_ecpu, t_egpu, t_route, t_p2p, t_attn, t_kvb, t_head;
uint64_t n_p2p; /* P0 execution profile: tier split + residual hops */
uint64_t cpu_expert_rows; int64_t cpu_expert_bytes;
/* profiling: dove va il tempo (wall del
* thread di compute; il servizio disco
* overlappato vive in g_edisk_ns) */
@@ -310,7 +311,7 @@ static void prof_lat(double s){ g_prof_lat[g_prof_nlat++ % PROF_LAT_CAP]=s; }
/* snapshot for windowed reports (serve mode: one report per turn) */
typedef struct {
double edisk,ewait,emm,ecpu,egpu,route,p2p,attn,head;
int64_t io; uint64_t hits,miss,ereq,n_fw,n_emit,nlat,n_p2p;
int64_t io,cpu_bytes; uint64_t hits,miss,ereq,n_fw,n_emit,nlat,n_p2p,cpu_rows;
} ProfBase;
static void prof_base(Model *m, ProfBase *b){
b->edisk=edisk_s(); b->ewait=m->t_ewait; b->emm=m->t_emm;
@@ -319,6 +320,7 @@ static void prof_base(Model *m, ProfBase *b){
b->io=atomic_load_explicit(&g_prof_io,memory_order_relaxed);
b->hits=m->hits; b->miss=m->miss; b->ereq=m->ereq;
b->n_fw=m->n_fw; b->n_emit=m->n_emit; b->nlat=g_prof_nlat; b->n_p2p=m->n_p2p;
b->cpu_bytes=m->cpu_expert_bytes;b->cpu_rows=m->cpu_expert_rows;
}
static float *falloc(int64_t n){
@@ -3277,7 +3279,9 @@ static void moe(Model *m, Layer *l, int layer, float *x, int S, float *out, int
matmul_qt(hh, gg, &e->d, nr);
for(int r=0;r<nr;r++){ float *os=out+(int64_t)rows[r]*D, wgt=rw[r], *hr=hh+(int64_t)r*D;
for(int d=0;d<D;d++) os[d]+=wgt*hr[d]; }
double dt=now_s()-t0;m->t_emm+=dt;if(g_prof)m->t_ecpu+=dt;
double dt=now_s()-t0;m->t_emm+=dt;if(g_prof){m->t_ecpu+=dt;
m->cpu_expert_bytes+=qt_bytes(&e->g)+qt_bytes(&e->u)+qt_bytes(&e->d);
m->cpu_expert_rows+=(uint64_t)nr;}
}
#ifdef COLI_CUDA
ColiCudaTensor *dev_g[COLI_CUDA_MAX_DEVICES][64],*dev_u[COLI_CUDA_MAX_DEVICES][64];
@@ -3320,6 +3324,8 @@ static void moe(Model *m, Layer *l, int layer, float *x, int S, float *out, int
expert_gate_up(gg,uu,xg,&e->g,&e->u,nr);
for(int64_t z=0;z<(int64_t)nr*I;z++) gg[z]=siluf(gg[z])*uu[z];
matmul_qt(hh,gg,&e->d,nr);
if(g_prof){m->cpu_expert_bytes+=qt_bytes(&e->g)+qt_bytes(&e->u)+qt_bytes(&e->d);
m->cpu_expert_rows+=(uint64_t)nr;}
}
if(g_prof)m->t_ecpu+=now_s()-tc;
}
@@ -4574,8 +4580,9 @@ static void profile_print(Model *m, double elapsed){
edisk_s(),m->t_ewait,m->t_emm,m->t_attn,m->t_kvb,m->t_head,elapsed-accounted);
printf("ATTENTION: projection/RoPE %.3fs | score-softmax-value %.3fs | output projection %.3fs\n",
m->t_aproj,m->t_acore,m->t_aout);
if(g_prof)printf("P0-EXEC: routed CPU %.3fs | routed GPU critical %.3fs | router %.3fs | residual P2P %.3fs / %llu hop | orchestration %.3fs\n",
m->t_ecpu,m->t_egpu,m->t_route,m->t_p2p,(unsigned long long)m->n_p2p,
if(g_prof)printf("P0-EXEC: routed CPU %.3fs / %.2f GB/s (%llu row) | routed GPU critical %.3fs | router %.3fs | residual P2P %.3fs / %llu hop | orchestration %.3fs\n",
m->t_ecpu,m->t_ecpu>0?m->cpu_expert_bytes/1e9/m->t_ecpu:0.0,
(unsigned long long)m->cpu_expert_rows,m->t_egpu,m->t_route,m->t_p2p,(unsigned long long)m->n_p2p,
elapsed-m->t_ewait-m->t_emm-m->t_attn-m->t_head-m->t_route-m->t_p2p>0?
elapsed-m->t_ewait-m->t_emm-m->t_attn-m->t_head-m->t_route-m->t_p2p:0);
#ifdef COLI_METAL
@@ -4592,6 +4599,7 @@ static void profile_print(Model *m, double elapsed){
static void profile_reset(Model *m){
m->t_ewait=m->t_emm=m->t_attn=m->t_kvb=m->t_head=0;
m->t_ecpu=m->t_egpu=m->t_route=m->t_p2p=0;m->n_p2p=0;
m->cpu_expert_bytes=0;m->cpu_expert_rows=0;
m->t_aproj=m->t_acore=m->t_aout=0;
atomic_store_explicit(&g_edisk_ns,0,memory_order_relaxed);
}
@@ -4639,15 +4647,18 @@ static void prof_report(Model *m, const ProfBase *b, double elapsed, int tokens,
double emm=m->t_emm-b->emm, ecpu=m->t_ecpu-b->ecpu, egpu=m->t_egpu-b->egpu;
double route=m->t_route-b->route,p2p=m->t_p2p-b->p2p;
uint64_t np2p=m->n_p2p-b->n_p2p;
int64_t cpu_bytes=m->cpu_expert_bytes-b->cpu_bytes;
uint64_t cpu_rows=m->cpu_expert_rows-b->cpu_rows;
double attn=m->t_attn-b->attn, head=m->t_head-b->head;
double other=elapsed-io_w-emm-attn-head-route-p2p; if(other<0) other=0;
double f_io=io_w/elapsed, f_emm=emm/elapsed, f_attn=attn/elapsed;
fprintf(f,"[PROF] time shares: expert-I/O %.0f%% | expert-matmul %.0f%% | attention %.0f%% | lm_head %.0f%% | other %.0f%%\n",
100*f_io,100*f_emm,100*f_attn,100*head/elapsed,100*other/elapsed);
double slow=ecpu>egpu?ecpu:egpu,fast=ecpu<egpu?ecpu:egpu;
fprintf(f,"[PROF] P0 execution: routed CPU %.3fs | routed GPU critical %.3fs | tier straggler %.2fx | "
fprintf(f,"[PROF] P0 execution: routed CPU %.3fs / %.2f GB/s (%llu row) | routed GPU critical %.3fs | tier straggler %.2fx | "
"router %.3fs | residual P2P %.3fs (%llu hop, %.3f ms/hop) | orchestration %.3fs\n",
ecpu,egpu,fast>1e-9?slow/fast:0.0,route,p2p,(unsigned long long)np2p,
ecpu,ecpu>0?cpu_bytes/1e9/ecpu:0.0,(unsigned long long)cpu_rows,
egpu,fast>1e-9?slow/fast:0.0,route,p2p,(unsigned long long)np2p,
np2p?p2p*1e3/np2p:0.0,other);
if(f_io>=0.30){
fprintf(f,"[PROF] verdict: I/O-bound — %.0f%% of the time waits on expert reads (hit %.0f%%).",100*f_io,hitp);
c/tests/test_benchmark_cuda_fixture.py
+2 -2
View File
@@ -6,7 +6,7 @@ from tools.benchmark_cuda_fixture import parse_output, parse_p0
SAMPLE = """
REPLAY decode: 4 tokens | 12.34 tok/s
PROFILE: expert-disk 1.25s | expert-matmul 2.50s | attention 0.75s | lm_head 0.10s | other -0.05s
P0-EXEC: routed CPU 1.200s | routed GPU critical 0.150s | router 0.200s | residual P2P 0.030s / 75 hop | orchestration 0.100s
P0-EXEC: routed CPU 1.200s / 123.40 GB/s (456 row) | routed GPU critical 0.150s | router 0.200s | residual P2P 0.030s / 75 hop | orchestration 0.100s
"""
@@ -21,7 +21,7 @@ class ParseOutputTest(unittest.TestCase):
parse_output("REPLAY decode: 4 tokens | 12.34 tok/s", "engine failed")
def test_extracts_p0_profile(self):
self.assertEqual(parse_p0(SAMPLE), [1.2, 0.15, 0.2, 0.03, 75.0, 0.1])
self.assertEqual(parse_p0(SAMPLE), [1.2, 123.4, 456.0, 0.15, 0.2, 0.03, 75.0, 0.1])
if __name__ == "__main__":
c/tools/benchmark_cuda_fixture.py
+3 -2
View File
@@ -18,10 +18,11 @@ PROFILE_RE = re.compile(
)
PROFILE_KEYS = ("disk", "expert_matmul", "attention", "lm_head", "other")
P0_RE = re.compile(
r"P0-EXEC: routed CPU ([0-9.]+)s \| routed GPU critical ([0-9.]+)s \| "
r"P0-EXEC: routed CPU ([0-9.]+)s / ([0-9.]+) GB/s \(([0-9]+) row\) \| routed GPU critical ([0-9.]+)s \| "
r"router ([0-9.]+)s \| residual P2P ([0-9.]+)s / ([0-9]+) hop \| orchestration ([0-9.]+)s"
)
P0_KEYS = ("routed_cpu", "routed_gpu_critical", "router", "p2p", "p2p_hops", "orchestration")
P0_KEYS = ("routed_cpu", "routed_cpu_gb_s", "routed_cpu_rows", "routed_gpu_critical",
"router", "p2p", "p2p_hops", "orchestration")
def parse_output(stdout: str, stderr: str = "") -> tuple[float, list[float]]: