# Dalek: An Unconventional and Energy-Aware Heterogeneous Cluster

arXiv: https://arxiv.org/abs/2508.10481 · HTML: https://mlsanity.com/paper/2508.10481/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Aug 2025.

## Built on by (most cited first, 2 of 2)

- [Benchmarking Deep Learning Convolutions on Energy-constrained CPUs](https://mlsanity.com/paper/2509.26217/) (2025)
- [Efficient Few-Shot Learning for Edge AI via Knowledge Distillation on MobileViT](https://mlsanity.com/paper/2603.26145/) (2026)

## Abstract (arXiv)

Dalek is an experimental compute cluster designed to evaluate the performance of heterogeneous, consumer-grade hardware for software design, prototyping, and algorithm development. In contrast to traditional computing centers that rely on costly, server-class components, Dalek integrates CPUs and GPUs typically found in mini-PCs, laptops, and gaming desktops, providing a cost-effective yet versatile platform. This document details the cluster's architecture and software stack, and presents results from synthetic benchmarks. Furthermore, it introduces a custom energy monitoring platform capable of delivering 1000 averaged samples per second with milliwatt-level resolution. This high-precision monitoring capability enables a wide range of energy-aware research experiments in applied Computer Science.