Compare commits

..

5 Commits
v7.16 ... v7.19

6 changed files with 84 additions and 23 deletions

1
.gitignore vendored
View File

@@ -2,3 +2,4 @@
.DS_Store
dist/
iso/out/
build-cache/

View File

@@ -1601,7 +1601,10 @@ func maxInt(a, b int) int {
// queryIPMIServerPowerW reads the current server power draw via ipmitool dcmi.
// Returns 0 and an error if IPMI is unavailable or the output cannot be parsed.
func queryIPMIServerPowerW() (float64, error) {
out, err := satExecCommand("ipmitool", "dcmi", "power", "reading").Output()
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
defer cancel()
cmd := exec.CommandContext(ctx, "ipmitool", "dcmi", "power", "reading")
out, err := cmd.Output()
if err != nil {
return 0, fmt.Errorf("ipmitool dcmi power reading: %w", err)
}
@@ -1620,6 +1623,7 @@ func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64,
}
deadline := time.Now().Add(time.Duration(durationSec) * time.Second)
var samples []float64
loop:
for {
if w, err := queryIPMIServerPowerW(); err == nil {
samples = append(samples, w)
@@ -1629,7 +1633,7 @@ func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64,
}
select {
case <-ctx.Done():
break
break loop
case <-time.After(2 * time.Second):
}
}

View File

@@ -81,8 +81,12 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
b.WriteString("\n")
}
// ── Scoring methodology ───────────────────────────────────────────────────
b.WriteString("## Scoring Methodology\n\n")
// ── Methodology ───────────────────────────────────────────────────────────
b.WriteString("## Methodology\n\n")
fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline -> warmup -> steady-state -> interconnect -> cooldown phases.\n", result.BenchmarkProfile)
b.WriteString("- Single-GPU compute score comes from `bee-gpu-burn` on the cuBLASLt path when available.\n")
b.WriteString("- Thermal and power limits are inferred from NVIDIA clock-event counters plus sustained telemetry.\n")
b.WriteString("- `result.json` is the canonical machine-readable source for the run.\n\n")
b.WriteString("**Compute score** is derived from two phases:\n\n")
b.WriteString("- **Synthetic** — each precision type (fp8, fp16, fp32, fp64, fp4) runs alone for a dedicated window. ")
b.WriteString("Measures peak throughput with the full GPU dedicated to one kernel type. ")
@@ -286,13 +290,6 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
}
}
// ── Methodology ───────────────────────────────────────────────────────────
b.WriteString("## Methodology\n\n")
fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline → warmup → steady-state → interconnect → cooldown phases.\n", result.BenchmarkProfile)
b.WriteString("- Single-GPU compute score from bee-gpu-burn cuBLASLt when available.\n")
b.WriteString("- Thermal and power limitations inferred from NVIDIA clock event reason counters and sustained telemetry.\n")
b.WriteString("- `result.json` is the canonical machine-readable source for this benchmark run.\n\n")
// ── Raw files ─────────────────────────────────────────────────────────────
b.WriteString("## Raw Files\n\n")
b.WriteString("- `result.json`\n- `report.md`\n- `summary.txt`\n- `verbose.log`\n")

View File

@@ -6,7 +6,7 @@ NCCL_CUDA_VERSION=13.0
NCCL_SHA256=2e6faafd2c19cffc7738d9283976a3200ea9db9895907f337f0c7e5a25563186
NCCL_TESTS_VERSION=2.13.10
NVCC_VERSION=12.8
CUBLAS_VERSION=13.0.2.14-1
CUBLAS_VERSION=13.1.1.3-1
CUDA_USERSPACE_VERSION=13.0.96-1
DCGM_VERSION=4.5.3-1
JOHN_JUMBO_COMMIT=67fcf9fe5a

View File

@@ -33,7 +33,6 @@ typedef void *CUstream;
#define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR 75
#define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR 76
#define MAX_STRESS_STREAMS 16
#define MAX_CUBLAS_PROFILES 5
#define MIN_PROFILE_BUDGET_BYTES ((size_t)4u * 1024u * 1024u)
#define MIN_STREAM_BUDGET_BYTES ((size_t)64u * 1024u * 1024u)
@@ -689,6 +688,8 @@ static const struct profile_desc k_profiles[] = {
#endif
};
#define PROFILE_COUNT ((int)(sizeof(k_profiles) / sizeof(k_profiles[0])))
static int load_cublaslt(struct cublaslt_api *api) {
memset(api, 0, sizeof(*api));
api->lib = dlopen("libcublasLt.so.13", RTLD_NOW | RTLD_LOCAL);
@@ -1124,7 +1125,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
const char *precision_filter,
struct stress_report *report) {
struct cublaslt_api cublas;
struct prepared_profile prepared[MAX_STRESS_STREAMS * MAX_CUBLAS_PROFILES];
struct prepared_profile prepared[MAX_STRESS_STREAMS * PROFILE_COUNT];
cublasLtHandle_t handle = NULL;
CUcontext ctx = NULL;
CUstream streams[MAX_STRESS_STREAMS] = {0};
@@ -1134,7 +1135,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
int active = 0;
int mp_count = 0;
int stream_count = 1;
int profile_count = (int)(sizeof(k_profiles) / sizeof(k_profiles[0]));
int profile_count = PROFILE_COUNT;
int prepared_count = 0;
size_t requested_budget = 0;
size_t total_budget = 0;
@@ -1159,6 +1160,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
return 0;
}
/* Count profiles matching the filter (for deciding what to run). */
for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc &&
(precision_filter == NULL || strcmp(k_profiles[i].block_label, precision_filter) == 0)) {
@@ -1172,18 +1174,31 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
return 0;
}
/* Count all profiles active on this GPU regardless of filter.
* Used as the budget divisor so matrix sizes stay consistent whether
* running all precisions together or a single-precision phase. */
int planned_total = 0;
for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc) {
planned_total++;
}
}
if (planned_total < planned) {
planned_total = planned;
}
requested_budget = (size_t)size_mb * 1024u * 1024u;
if (requested_budget < (size_t)planned * MIN_PROFILE_BUDGET_BYTES) {
requested_budget = (size_t)planned * MIN_PROFILE_BUDGET_BYTES;
if (requested_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
requested_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
}
total_budget = clamp_budget_to_free_memory(cuda, requested_budget);
if (total_budget < (size_t)planned * MIN_PROFILE_BUDGET_BYTES) {
total_budget = (size_t)planned * MIN_PROFILE_BUDGET_BYTES;
if (total_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
total_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
}
if (query_multiprocessor_count(cuda, dev, &mp_count) &&
cuda->cuStreamCreate &&
cuda->cuStreamDestroy) {
stream_count = choose_stream_count(mp_count, planned, total_budget, 1);
stream_count = choose_stream_count(mp_count, planned_total, total_budget, 1);
}
if (stream_count > 1) {
int created = 0;
@@ -1196,7 +1211,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
}
}
report->stream_count = stream_count;
per_profile_budget = total_budget / ((size_t)planned * (size_t)stream_count);
per_profile_budget = total_budget / ((size_t)planned_total * (size_t)stream_count);
if (per_profile_budget < MIN_PROFILE_BUDGET_BYTES) {
per_profile_budget = MIN_PROFILE_BUDGET_BYTES;
}
@@ -1424,7 +1439,17 @@ int main(int argc, char **argv) {
ok = run_cublaslt_stress(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, precision_filter, &report);
#endif
if (!ok) {
if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, &report)) {
if (precision_filter != NULL) {
fprintf(stderr,
"requested precision path unavailable: precision=%s device=%s cc=%d.%d\n",
precision_filter,
name,
cc_major,
cc_minor);
return 1;
}
int ptx_mb = size_mb;
if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, ptx_mb, &report)) {
return 1;
}
}

View File

@@ -873,9 +873,37 @@ if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
CUBLAS_CACHE="${DIST_DIR}/cublas-${CUBLAS_VERSION}+cuda${NCCL_CUDA_VERSION}"
echo "=== bee-gpu-burn FP4 header probe ==="
fp4_type_match="$(grep -Rsnm 1 'CUDA_R_4F_E2M1' "${CUBLAS_CACHE}/include" 2>/dev/null || true)"
fp4_scale_match="$(grep -Rsnm 1 'CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3' "${CUBLAS_CACHE}/include" 2>/dev/null || true)"
if [ -n "$fp4_type_match" ]; then
echo "fp4_header_symbol=present"
echo "$fp4_type_match"
else
echo "fp4_header_symbol=missing"
fi
if [ -n "$fp4_scale_match" ]; then
echo "fp4_scale_mode_symbol=present"
echo "$fp4_scale_match"
else
echo "fp4_scale_mode_symbol=missing"
fi
GPU_STRESS_NEED_BUILD=1
if [ -f "$GPU_BURN_WORKER_BIN" ] && [ "${BUILDER_DIR}/bee-gpu-stress.c" -ot "$GPU_BURN_WORKER_BIN" ]; then
if [ -f "$GPU_BURN_WORKER_BIN" ]; then
GPU_STRESS_NEED_BUILD=0
for dep in \
"${BUILDER_DIR}/bee-gpu-stress.c" \
"${BUILDER_DIR}/VERSIONS"; do
if [ "$dep" -nt "$GPU_BURN_WORKER_BIN" ]; then
GPU_STRESS_NEED_BUILD=1
break
fi
done
if [ "$GPU_STRESS_NEED_BUILD" = "0" ] && \
find "${CUBLAS_CACHE}/include" "${CUBLAS_CACHE}/lib" -type f -newer "$GPU_BURN_WORKER_BIN" | grep -q .; then
GPU_STRESS_NEED_BUILD=1
fi
fi
if [ "$GPU_STRESS_NEED_BUILD" = "1" ]; then
@@ -889,6 +917,12 @@ if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
else
echo "=== bee-gpu-burn worker up to date, skipping build ==="
fi
echo "=== bee-gpu-burn compiled profile probe ==="
if grep -aq 'fp4_e2m1' "$GPU_BURN_WORKER_BIN"; then
echo "fp4_profile_string=present"
else
echo "fp4_profile_string=missing"
fi
fi
echo "=== preparing staged overlay (${BUILD_VARIANT}) ==="