Project Proposal: Exploration of Energy Efficiency in x86, ARM, and GPU Architectures

Introduction

The energy consumption of computer systems is a significant concern, and different architectures, such as x86, ARM, and GPU, have been proposed to improve energy efficiency. This project aims to investigate the energy efficiency of x86, ARM, and GPU architectures and identify the most promising solutions with a specific focus on the thermal effects of power consumption and cooling requirements for high-performance devices.

Motivation & Background

Energy efficiency is an important consideration for computer systems as it can lead to reduced energy consumption and costs. This is particularly important for large-scale systems, such as data centers, where energy consumption can be a major expense. Additionally, reducing energy consumption can also help to reduce environmental impact. The thermal effects of power consumption and cooling requirements are also important factors to consider, as high-performance devices such as GPUs can generate a significant amount of heat and require specialized cooling systems.

The Verge has reports of power cables burning or melting on the new high-end Nvidia RTX 4090 graphics card, highlighting the potential dangers of high power consumption and inadequate cooling. The issue has been linked to the new 12VHPWR adapter cable that Nvidia ships with the RTX 4090, which is designed for new ATX 3.0 power supplies. The connector and terminals are smaller than previous generations, and there are concerns that bending the cables too close to the connector could result in damage. This issue is not only with Nvidia but with other vendors as well. [1]

It's important to consider the potential issues that can arise from high power consumption and inadequate cooling, and to investigate potential solutions to improve energy efficiency and prevent these types of incidents from occurring.

What Is Being Covered

This project will cover the following areas:

  1. A survey of current research on energy efficiency in x86, ARM, and GPU architectures, with a focus on the thermal effects of power consumption and cooling requirements.
  2. A comparison of the energy consumption and thermal performance of x86, ARM, and GPU architectures when running different types of workloads.
  3. Identification of the strengths and weaknesses of each architecture in terms of energy efficiency.
  4. An investigation of potential solutions to improve the energy efficiency of existing architectures.

Objectives

  1. Conduct a survey of current research on energy efficiency in x86, ARM, and GPU architectures with a focus on the thermal effects of power consumption and cooling requirements.
  2. Compare the energy consumption and thermal performance of x86, ARM, and GPU architectures when running different types of workloads.
  3. Identify the strengths and weaknesses of each architecture in terms of energy efficiency.
  4. Investigate potential solutions to improve the energy efficiency of existing architectures.

Methods

  1. Conduct a literature review of current research on energy efficiency in x86, ARM, and GPU architectures, with a focus on the thermal effects of power consumption and cooling requirements.
  2. Use benchmarking tools to compare the energy consumption and thermal performance of x86, ARM, and GPU architectures when running different types of workloads.
  3. Identify the strengths and weaknesses of each architecture in terms of energy efficiency by profiling their performance on different workloads.
  4. Investigate potential solutions by implementing and testing them on different workloads.

Expected Outcomes

  1. A comprehensive survey of current research on energy efficiency in x86, ARM, and GPU architectures with a focus on the thermal effects of power consumption and cooling requirements.
  2. A detailed comparison of the energy consumption and thermal performance of x86, ARM, and GPU architectures when running different types of workloads.
  3. Identification of the strengths and weaknesses of each architecture in terms of energy efficiency.

Distribution of Work

Name Responsibility
Anthony Kung Research & Comparison Testing
Wilhelm Gusztav Research & Project Management
Nat Bourassa Research & Results Analysis

Timeline

Week 5: Research Deadline

Week 7: Architecture Comparisons

Mid-Report Deadline

Week 8: Result Consolidation

Week 9: Final Revised Paper Finish

References

[1] T. Warren, "Nvidia investigating reports of RTX 4090 power cables burning or melting," The Verge, 25-Oct-2022.