Evaluates the energy proportionality and power efficiency of enterprise server subsystems under varying JVM-based web service workloads. It measures how power consumption scales with workload intensity and identifies non-proportional power draw in uncore components. Use when the user wants to benchmark on SPECpower_ssj2008, or asks about evaluating this task. Reports watts.
Scanned 9/11/2026
Install to Claude Code
npx -y skills add qhjqhj00/research-skills-pool --skill specpower-eval --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Specpower Eval?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/qhjqhj00-specpower-eval)More formats (shields.io, HTML) on the badges page.
---
name: specpower-eval
description: Evaluates the energy proportionality and power efficiency of enterprise server subsystems under varying JVM-based web service workloads. It measures how power consumption scales with workload intensity and identifies non-proportional power draw in uncore components. Use when the user wants to benchmark on SPECpower_ssj2008, or asks about evaluating this task. Reports watts.
metadata:
skill_kind: dataset_eval
source_arxiv: 1501.02724
bibtex_key: subramaniam2015towards
confidence: high
---
# specpower-eval
> Towards Energy-Proportional Computing Using Subsystem-Level Power Management — Subramaniam and Feng (2015) (arXiv:1501.02724, 2015)
## What this evaluates
Evaluates the energy proportionality and power efficiency of enterprise server subsystems under varying JVM-based web service workloads. It measures how power consumption scales with workload intensity and identifies non-proportional power draw in uncore components.
## Datasets
- **SPECpower_ssj2008** — total ?; splits: test (-1)
## Metrics
- `watts` **(primary)** — range: watts
- Measured directly using a Yokogawa WT210 power meter at the system level. Reported at idle and at 100% load-level (target 1,120,000 ssj_ops).
## Input / output format
**Input**: System Under Test (Intel Xeon E5-2665, 256 GB RAM, Linux 3.2.0) running 8 JVMs with 4 threads each, pinned to adjacent physical cores, with HugeTLB enabled.
**Output**: Power consumption readings in watts, throughput in ssj_ops, and response time compliance metrics.
## Scoring recipe
```python
power_idle = measure_power()
power_peak = measure_power_at_load(100)
throughput = get_throughput() # ssj_ops
energy_prop = power_idle / power_peak
return power_idle, power_peak, throughput, energy_prop
```
## Common pitfalls
- Uncore subsystem power remains constant regardless of workload load, skewing energy proportionality calculations if only core power is considered.
- Idle power consumption is significant (36–55% of peak), contradicting assumptions of near-zero idle power in traditional servers.
- Disk I/O must be eliminated (using RAMFS) to isolate processor and memory power management effects.
## Evidence (verbatim from paper)
> On an average, the SUT consumes 120 watts at idle and 330 watts at 100% load-level of SPECpower.
## Citation
```bibtex
@misc{subramaniam2015towards,
title={Towards Energy-Proportional Computing Using Subsystem-Level Power Management},
author={Subramaniam and Feng (2015)},
year={2015},
note={arXiv:1501.02724}
}
```
- arXiv: 1501.02724
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!