A job needs part CPU and part GPU, what shape do you pick?

When selecting a shape for a job that requires both CPU and GPU resources, the DenseIO configuration is often the most suitable choice. DenseIO shapes are specifically designed to deliver high input/output operations per second (IOPS) and are equipped with enhanced networking capabilities, which are beneficial for workloads that require significant data throughput and processing power.

These instances typically combine high-performance storage options—like SSDs—with CPU capabilities, making them suitable for tasks that involve both computationally intensive operations and large-scale data processing. This is particularly useful for applications such as machine learning, deep learning, or any scenario where processing large datasets and performing complex calculations concurrently is essential.

On the other hand, shapes designed for Compute Optimized, Memory Optimized, or Storage Optimized workloads focus on specific areas; these configurations might lack the balanced capabilities needed for jobs requiring simultaneous CPU and GPU resources. Compute Optimized might offer strong CPU performance but not necessarily the GPU component, while Memory Optimized focuses on large memory allocations, and Storage Optimized emphasizes high throughput for storage operations. Thus, DenseIO is the most effective choice for a hybrid workload that needs both types of processing power.