From 4799058b0bab1d3a3d8cdfd968e857899bfac7cc Mon Sep 17 00:00:00 2001
From: mafooq <mafoqulhassan@gmail.com>
Date: Thu, 10 Jul 2025 09:12:18 +0000
Subject: [PATCH] Feat#3: Fixed L3 cache parsing and added FLOPs annotation
---
src/hypertool/utils.py | 37 +++++++++++++++++++++++--------------
1 file changed, 23 insertions(+), 14 deletions(-)
diff --git a/src/hypertool/utils.py b/src/hypertool/utils.py
index b794546..135e8f5 100644
--- a/src/hypertool/utils.py
+++ b/src/hypertool/utils.py
@@ -143,17 +143,26 @@ def extract_cpu_features():
elif "CPU max MHz" in line:
features["Clock (GHz)"] = round(float(line.split(":")[1].strip()) / 1000, 2)
elif "L3 cache" in line:
- value = line.split(":")[1].strip()
- if value.endswith("K"):
- features["L3_Cache"] = round(int(value[:-1]) / 1024, 2)
- elif value.endswith("M"):
- features["L3_Cache"] = float(value[:-1])
- else:
- features["L3_Cache"] = 0.0
-
- features.setdefault("Cores", os.cpu_count() or 4)
- features.setdefault("Clock (GHz)", 2.5)
- features.setdefault("L3_Cache", 8.0)
+ value = line.split(":")[1].strip().split()[0] # take first numeric part
+ value = re.sub(r"[^\d.]", "", value) # keep digits and dot only
+ try:
+ features["L3_Cache"] = float(value)
+ except ValueError:
+ features["L3_Cache"] = 8.0 # fallback
+
+ features.setdefault("Cores", os.cpu_count() or 4) # Use actual core count or 4 core median configuration
+ features.setdefault(
+ "Clock (GHz)", 2.5
+ ) # Conservative estimate for modern CPUs (average clock rate between AMD and Intel CPUs)
+ features.setdefault("L3_Cache", 8.0) # Typical L3 cache size for mid-tier CPUs
+
+ # Fallback Values Justification:
+ # ------------------------------
+ # Cores: 4 — Median logical core count for laptops, desktops, and cloud VMs
+ # Clock: 2.5 GHz — Conservative base frequency across modern CPUs
+ # L3 Cache: 8.0 MB — Common shared L3 cache size in mid-range CPUs
+ # These defaults ensure realistic performance estimation without exaggeration
+ # in case of parsing or access errors.
return features
except Exception as e:
@@ -197,7 +206,7 @@ def get_energy_efficiency_annotation():
cpu_model = get_cpu_model()
tdp = get_tdp(cpu_model)
if not tdp:
- return {"hyperai.eu/node-energy-efficiency": "unknown"}
+ return {"hyperai.eu/node-energy-efficiency": "unknown", "hyperai.eu/node-flops-per-sec": "unknown"}
a = np.random.rand(1_000_000).astype(np.float32)
b = np.random.rand(1_000_000).astype(np.float32)
@@ -220,8 +229,8 @@ def get_energy_efficiency_annotation():
else:
label = "very high"
- return {"hyperai.eu/node-energy-efficiency": label}
+ return {"hyperai.eu/node-energy-efficiency": label, "hyperai.eu/node-flops-per-sec": round(flops_per_sec, 2)}
except Exception as e:
logging.error(f"Failed energy estimation: {e}")
- return {"hyperai.eu/node-energy-efficiency": "unknown"}
+ return {"hyperai.eu/node-energy-efficiency": "unknown", "hyperai.eu/node-flops-per-sec": "unknown"}
--
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