Benchmark: parallel GPU mode, resilient inventory query, server model in results

- Add parallel GPU mode (checkbox, off by default): runs all selected GPUs
  simultaneously via a single bee-gpu-burn invocation instead of sequentially;
  per-GPU telemetry, throttle counters, TOPS, and scoring are preserved
- Make queryBenchmarkGPUInfo resilient: falls back to a base field set when
  extended fields (attribute.multiprocessor_count, power.default_limit) cause
  exit status 2, preventing lgc normalization from being silently skipped
- Log explicit "graphics clock lock skipped" note when inventory is unavailable
- Collect server model from DMI (/sys/class/dmi/id/product_name) and store in
  result JSON; benchmark history columns now show "Server Model (N× GPU Model)"
  grouped by server+GPU type rather than individual GPU index

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

audit/internal/webui/tasks.go

@@ -123,6 +123,7 @@ type taskParams struct {
 	BurnProfile        string   `json:"burn_profile,omitempty"`
 	BenchmarkProfile   string   `json:"benchmark_profile,omitempty"`
 	RunNCCL            bool     `json:"run_nccl,omitempty"`
+	ParallelGPUs       bool     `json:"parallel_gpus,omitempty"`
 	DisplayName        string   `json:"display_name,omitempty"`
 	Device             string   `json:"device,omitempty"` // for install
 	PlatformComponents []string `json:"platform_components,omitempty"`
@@ -585,6 +586,7 @@ func (q *taskQueue) runTask(t *Task, j *jobState, ctx context.Context) {
 			GPUIndices:        t.params.GPUIndices,
 			ExcludeGPUIndices: t.params.ExcludeGPUIndices,
 			RunNCCL:           t.params.RunNCCL,
+			ParallelGPUs:      t.params.ParallelGPUs,
 		}, j.append)
 	case "nvidia-compute":
 		if a == nil {