High-Performance Computing: Cloud Vs. Bare Metal

Advanced computational problems require the ability to process data and perform complex calculations at high speeds. This is commonly known as high performance computing or HPC. Getting the most from HPC requires choosing the right environment for each application. With that in mind, here is a quick guide to HPC cloud and HPC bare metal.

High-performance computing (HPC) cloud

HPC cloud offers unmatched scalability and flexibility, making it ideal for variable workloads and short-term projects.

Performance

HPC cloud environments leverage virtualized infrastructure with varying degrees of isolation and resource dedication. While cloud instances provide high computational power, performance can be affected by the underlying virtualization layer, leading to slight overhead compared to bare metal solutions.

That said, advancements such as AWS Nitro and Azure’s HPC Cache have mitigated these issues, offering near-bare-metal performance. The performance variability in cloud environments can also be influenced by the shared nature of physical hardware, leading to potential “noisy neighbor” problems where resource contention may occur, impacting the predictability of performance.

Cost

HPC cloud typically uses resource-based pricing, offering flexibility but potentially leading to high expenses for sustained workloads. Cloud providers do, however, usually offer various pricing tiers, including on-demand, reserved instances, and spot instances, allowing users to balance cost and performance based on their requirements.

While HPC cloud can be cost-effective for short-term or variable workloads, long-term use cases often result in significant costs, especially when factoring in data transfer fees, storage, and the need for persistent high-performance resources.

Scalability

HPC cloud environments excel in scalability, enabling rapid provisioning of thousands of cores and petabytes of storage within minutes. This elasticity is crucial for applications requiring dynamic resource scaling, such as computational fluid dynamics (CFD) simulations or genome sequencing, where the workload can be distributed across many nodes.

The scalability in cloud environments is virtually unlimited, constrained only by the user’s budget and the cloud provider’s resource availability. Moreover, cloud platforms offer integrated services like autoscaling and load balancing, which further enhance the scalability of HPC applications.

Use cases

HPC cloud is ideal for use cases requiring on-demand resource availability and rapid scalability. It is commonly used in industries like finance for risk modeling, in pharmaceuticals for drug discovery, and in media for rendering complex visual effects.

The cloud is also favored in academic research, where the need for temporary high-performance environments does not justify the cost of maintaining a dedicated HPC infrastructure.

Additionally, machine learning and AI workloads are increasingly migrating to cloud HPC environments due to the seamless integration with data services and the availability of specialized hardware like TPUs.

High-performance computing (HPC) bare metal

HPC bare metal provides the highest levels of performance and control. This makes it the preferred choice for consistent, high-demand computational tasks.

Performance

The performance of bare metal HPC systems is unmatched due to the absence of a virtualization layer, allowing direct access to the hardware. This setup minimizes latency and maximizes throughput, making it suitable for highly parallelized workloads that require consistent performance across many nodes.

Additionally, bare metal environments can be customized with specific hardware configurations tailored to the application’s needs, such as high-memory nodes, specialized accelerators like GPUs or FPGAs, and low-latency interconnects like InfiniBand.

Cost

The cost of bare metal HPC solutions involves significant upfront capital expenditure (CapEx) for hardware acquisition, maintenance, and energy consumption. Operational expenses (OpEx) are also higher compared to cloud environments due to the need for dedicated data center space, cooling, and personnel to manage the infrastructure.

That said, for organizations with continuous, high-intensity computational workloads, bare metal HPC can be more cost-effective in the long run compared to cloud solutions, as the fixed costs can be amortized over time, and there are no recurring rental fees. The trade-off is between upfront investment and long-term operational control and cost efficiency.

Scalability

Scalability in bare metal environments is limited by physical resources and the ability to provision additional hardware. Scaling up requires purchasing and integrating new hardware, which can be time-consuming and costly.

While horizontal scaling (adding more nodes) and vertical scaling (upgrading individual nodes) are both possible, they are constrained by physical space, power availability, and budget.

Bare metal environments do, however, excel in scaling within the designed capacity, ensuring consistent performance without the overhead associated with cloud-based solutions. Additionally, they offer more predictable performance, as there is no risk of resource contention from other tenants.

Use cases

HPC bare metal is typically used in scenarios where performance, control, and predictability are paramount. This includes scientific research requiring extensive simulations, such as climate modeling, astrophysics, and materials science.

Industries like aerospace and automotive engineering also rely heavily on bare metal HPC for computational fluid dynamics and finite element analysis. Moreover, financial services that demand ultra-low latency for high-frequency trading systems prefer bare metal environments.

Large enterprises with consistent HPC needs, such as oil and gas exploration or weather forecasting, often invest in bare metal infrastructure to maintain full control over their computational resources.