The Power of Ampere's ARM-Based Workloads on OCI: Outperforming AMD and Intel with Cost-Effective Solutions

Introduction

With the rapid advancement in technology and the constant need for increased computing power, businesses are always on the lookout for the best solutions to optimize their workloads. In recent years, Ampere's ARM-based processors have emerged as a strong competitor to the x86 architecture, traditionally dominated by AMD and Intel. Oracle Cloud Infrastructure (OCI) has had support for Ampere's ARM-based processors since 2021 and we are seeing an explosive trend in workload evaluations for this chipset. If you haven't considered evaluating your workloads for a more cost effective way to run them, in this article, I will discuss the benefits of running Ampere's ARM-based workloads on OCI and compare it to AMD and Intel solutions, with a focus on performance and pricing.

The Benefits of Running Ampere's ARM-Based Workloads on OCI

1. Performance

Ampere's ARM-based processors, such as the Altra series, are designed to deliver high-performance, predictable computing at scale. With up to 80 cores per processor, Ampere provides powerful parallelism and scalability, ensuring seamless execution of even the most demanding workloads. OCI's support for these processors allows businesses to harness this power for their cloud-based applications, outperforming equivalent x86 offerings from AMD and Intel.

2. Energy Efficiency

Ampere's ARM-based processors consume significantly less power than their x86 counterparts, leading to lower operational costs and a reduced carbon footprint. By choosing Ampere processors on OCI, businesses can not only enjoy the high-performance computing capabilities but also contribute to a greener and more sustainable environment.

3. Flexibility

OCI's support for Ampere's ARM-based processors offers businesses a wide range of choices for their infrastructure needs. This flexibility allows companies to select the right combination of compute, storage, and networking resources, ultimately optimizing their workloads according to their specific requirements.

4. Ecosystem and Compatibility

The ARM ecosystem has been growing rapidly, with major operating systems and software vendors providing support for ARM architecture. As a result, businesses can easily migrate or develop their applications to run on Ampere's ARM-based processors without worrying about compatibility issues.

Pricing Examples

Let's compare the pricing of Ampere's ARM-based solutions on OCI with equivalent AMD and Intel offerings.

1. Ampere Altra on OCI

OCI offers the Ampere Altra A1 Compute instances, starting at $0.01 per OCPU per hour for a flexible instance with 1 OCPU and 6 GB of memory. This pricing is highly competitive, considering the performance capabilities and energy efficiency of the Ampere Altra processors.

2. AMD EPYC on OCI

For comparison, OCI's AMD EPYC-based E4 instances start at $0.03 per OCPU per hour for a flexible instance with 1 OCPU and 8 GB of memory. While AMD EPYC processors deliver impressive performance, they consume more power than Ampere's ARM-based processors, leading to higher operational costs.

3. Intel Xeon on OCI

Intel Xeon-based instances on OCI, such as the X7 series, start at $0.045 per OCPU per hour for a flexible instance with 1 OCPU and 7.5 GB of memory. While Intel Xeon processors have long been considered the industry standard, their higher power consumption and pricing make them a less attractive option compared to Ampere's ARM-based processors.

Conclusion

By running Ampere's ARM-based workloads on OCI, businesses can take advantage of the high-performance computing capabilities, energy efficiency, flexibility, and growing ecosystem that these processors offer. Furthermore, the competitive pricing of Ampere Altra A1 Compute instances on OCI makes them a cost-effective alternative to traditional AMD and Intel-based solutions. As the ARM ecosystem continues to expand and gain momentum, companies should consider exploring Ampere's ARM-based processors on OCI to optimize their workloads and achieve better performance at a lower cost.