fix(agent): carry Intel GPU averages forward between samples (#2256)

Intel GPUs (intel_gpu_top) never report temperature or memory, so the
"suspended card" heuristic in calculateGPUAverage (temp == 0 &&
memoryUsed == 0) fired on every collection that landed between samples.

intel_gpu_top samples every 3.3s (intelGpuStatsInterval) while the hub's
realtime worker collects every 1s, so most realtime collections had no
new sample (delta count 0) and returned an empty GPUData with power
omitted (json "p"/"pp" are omitempty). The frontend derives the GPU
Power Draw series and legend from the latest sample, so the chart and
legend blanked on roughly two of every three or four one-second cycles.

NVIDIA/AMD were unaffected because they report temperature even when
idle, so the heuristic never fired and the last average was already
carried forward.

Gate the zero-return on non-engine (discrete) GPUs so Intel GPUs carry
the last average forward during between-sample gaps, matching the
existing NVIDIA/AMD behavior. Add a regression test.

agent/gpu.go

@@ -361,12 +361,16 @@ func (gm *GPUManager) calculateGPUAverage(id string, gpu *system.GPUData, cacheK
 
 	// If no new data arrived
 	if deltaCount == 0 {
-		// If GPU appears suspended (instantaneous values are 0), return zero values
-		// Otherwise return last known average for temporary collection gaps
-		if gpu.Temperature == 0 && gpu.MemoryUsed == 0 {
+		// Only discrete GPUs report temp/memory, so treat all-zero as suspended (return zeros).
+		// Engine-based (Intel) GPUs don't, so carry the last average forward across sample gaps.
+		if gpu.Engines == nil && gpu.Temperature == 0 && gpu.MemoryUsed == 0 {
 			return system.GPUData{Name: gpu.Name}
 		}
-		return gm.lastAvgData[id] // zero value if not found
+		lastAvg := gm.lastAvgData[id] // zero value if not found
+		if lastAvg.Name == "" {
+			lastAvg.Name = gpu.Name
+		}
+		return lastAvg
 	}
 
 	// Calculate new average

agent/gpu_test.go

@@ -566,6 +566,42 @@ func TestGetCurrentData(t *testing.T) {
 		assert.EqualValues(t, 2, gm.GpuDataMap["0"].Count, "Count should still be 2")
 	})
 
+	t.Run("carries Intel GPU average forward between samples", func(t *testing.T) {
+		// Intel GPUs report no temp/memory, so between-sample gaps (delta 0) must
+		// reuse the last average instead of returning zeros and blanking the chart.
+		gm := &GPUManager{
+			GpuDataMap: map[string]*system.GPUData{
+				"0": {
+					Name:     "GPU",
+					Usage:    0,   // derived from engines for Intel
+					Power:    200, // averages to 100 over 2 counts
+					PowerPkg: 60,  // averages to 30 over 2 counts
+					Count:    2,
+					Engines: map[string]float64{
+						"Render/3D": 80, // averages to 40
+						"Video":     20, // averages to 10
+					},
+				},
+			},
+		}
+
+		cacheKey := uint16(1000) // realtime cache key
+
+		// First collection - computes and stores averages
+		result1 := gm.GetCurrentData(cacheKey)
+		assert.InDelta(t, 100.0, result1["0"].Power, 0.01)
+		assert.InDelta(t, 30.0, result1["0"].PowerPkg, 0.01)
+		assert.InDelta(t, 40.0, result1["0"].Engines["Render/3D"], 0.01)
+
+		// Second collection with no new sample (count unchanged, temp/mem still 0).
+		// Must carry the last average forward rather than blanking to zero.
+		result2 := gm.GetCurrentData(cacheKey)
+		assert.Equal(t, "GPU", result2["0"].Name, "Name should be preserved")
+		assert.InDelta(t, 100.0, result2["0"].Power, 0.01, "Should reuse last average power, not 0")
+		assert.InDelta(t, 30.0, result2["0"].PowerPkg, 0.01, "Should reuse last average package power, not 0")
+		assert.InDelta(t, 40.0, result2["0"].Engines["Render/3D"], 0.01, "Should reuse last average engine usage")
+	})
+
 	t.Run("tracks separate averages per cache key", func(t *testing.T) {
 		gm := &GPUManager{
 			GpuDataMap: map[string]*system.GPUData{