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Compute optimized instances

Compute optimized instances are ideal for compute-bound applications that benefit from high-performance processors.

Bare metal instances, such as c5.metal, provide your applications with direct access to physical resources of the host server, such as processors and memory.

For more information, see Amazon EC2 C6i Instances.

C7a instances

These instances are powered by 4th generation AMD EPYC processors and are ideal for running advanced, compute-intensive workloads, such as the following:

For more information, see Amazon EC2 C7a instances.

C7g and C7gd instances

These instances are powered by Amazon Graviton3 processors and are ideal for running advanced, compute-intensive workloads, such as the following:

For more information, see Amazon EC2 C7g instances.

C7gn instances

Featuring the new Amazon Nitro Cards, C7gn instances deliver the highest network bandwidth, and the best packet-processing performance for Graviton-based Amazon EC2 instances. C7gn instances offer up to 200 Gbps network bandwidth and up to 50 percent higher packet-processing performance compared to previous generation C6gn instances. C7gn instances are ideal for network-intensive workloads, including:

For more information, see Amazon EC2 C7gn instances.

C7i instances

C7i instances are ideal for running compute intensive workloads, such as batch processing, machine learning, high end gaming, ad serving, and video encoding.

For more information, see Amazon EC2 C7i instances.

Hpc7g instances

Hpc7g instances are powered by Amazon Graviton3E processors and the next generation Amazon Nitro Card. They deliver 200 Gbps advanced networking with Elastic Fabric Adapter (EFA) for low latency and high network performance.

Hpc7g instances are ideal for running compute-intensive HPC applications that benefit from compute and memory bandwidth performance and low network latency, such as computational fluid dynamics, molecular dynamics, and weather simulations.

For more information, see Amazon EC2 Hpc7g instances.

Hpc7a instances

These instances feature up to 300 Gbps networking bandwidth with Elastic Fabric Adapter (EFA) for low latency and high network performance with Message Passing Interface (MPI). They feature up to 192 CPU cores with up to 768 GB of system memory.

Hpc7a instances are ideal for running compute-intensive HPC applications, such as computational fluid dynamics, molecular dynamics, and weather simulations that benefit from large core counts per instance and low network latency.

For more information, see Amazon EC2 Hpc7a instances.

Hardware specifications

The following is a summary of the hardware specifications for compute optimized instances. A virtual central processing unit (vCPU) represents a portion of the physical CPU assigned to a virtual machine (VM). For x86 instances, there are two vCPUs per core. For Graviton instances, there is one vCPU per core.

The compute optimized instances use the following processors.

For more information, see Amazon EC2 Instance Types.

Instance performance

EBS-optimized instances enable you to get consistently high performance for your EBS volumes by eliminating contention between Amazon EBS I/O and other network traffic from your instance. Some compute optimized instances are EBS-optimized by default at no additional cost. For more information, see Amazon EBS–optimized instances.

Network performance

You can enable enhanced networking on supported instance types to provide lower latencies, lower network jitter, and higher packet-per-second (PPS) performance. Most applications do not consistently need a high level of network performance, but can benefit from access to increased bandwidth when they send or receive data. For more information, see Enhanced networking on Windows.

The following is a summary of network performance for compute optimized instances that support enhanced networking.

For 32xlarge and metal instance types that support 200 Gbps, at least 2 ENIs, each attached to a different network card, are required on the instance to achieve 200 Gbps throughput. Each ENI attached to a network card can achieve a max of 170 Gbps.

The following table shows the baseline and burst bandwidth for instance types that use the network I/O credit mechanism to burst beyond their baseline bandwidth.

Amazon EBS I/O performance

Amazon EBS optimized instances use an optimized configuration stack and provide additional, dedicated capacity for Amazon EBS I/O. This optimization provides the best performance for your Amazon EBS volumes by minimizing contention between Amazon EBS I/O and other traffic from your instance.

For more information, see Amazon EBS–optimized instances.

SSD-based instance store volume I/O performance

If you use all the SSD-based instance store volumes available to your instance, you can get up to the IOPS (4,096 byte block size) performance listed in the following table (at queue depth saturation). Otherwise, you get lower IOPS performance.

As you fill the SSD-based instance store volumes for your instance, the number of write IOPS that you can achieve decreases. This is due to the extra work the SSD controller must do to find available space, rewrite existing data, and erase unused space so that it can be rewritten. This process of garbage collection results in internal write amplification to the SSD, expressed as the ratio of SSD write operations to user write operations. This decrease in performance is even larger if the write operations are not in multiples of 4,096 bytes or not aligned to a 4,096-byte boundary. If you write a smaller amount of bytes or bytes that are not aligned, the SSD controller must read the surrounding data and store the result in a new location. This pattern results in significantly increased write amplification, increased latency, and dramatically reduced I/O performance.

SSD controllers can use several strategies to reduce the impact of write amplification. One such strategy is to reserve space in the SSD instance storage so that the controller can more efficiently manage the space available for write operations. This is called over-provisioning. The SSD-based instance store volumes provided to an instance don't have any space reserved for over-provisioning. To reduce write amplification, we recommend that you leave 10% of the volume unpartitioned so that the SSD controller can use it for over-provisioning. This decreases the storage that you can use, but increases performance even if the disk is close to full capacity.

For instance store volumes that support TRIM, you can use the TRIM command to notify the SSD controller whenever you no longer need data that you've written. This provides the controller with more free space, which can reduce write amplification and increase performance. For more information, see Instance store volume TRIM support.

Release notes