Characterizing performant infrastructure for large-scale algorithms

To efficiently run large-scale algorithms, we want performant systems as they are designed to handle increased workloads by adding more computing resources to distribute the processing. Horizontal scaling is a key technique for achieving scalability in distributed systems, enabling the system to expand its capacity by allocating tasks to multiple resources. These resources are typically hardware (like Central Processing Units (CPUs) or GPUs) or software elements (like memory, disk space, or network bandwidth) that the system can utilize to perform tasks. For a scalable system to efficiently address computational requirements, it should exhibit elasticity and load balancing, as discussed in the following section.

Elasticity

Elasticity refers to the capacity of infrastructure to dynamically scale resources according to changing requirements. One common method of implementing this feature is autoscaling, a prevalent...