This is the Electe Review. Today, high performance computing is not a lab problem, it is a management problem, and most SMEs are already paying for it without knowing it. Here is the core argument. For small and medium-sized businesses, the limiting factor in analytics is rarely data. It is computation time. When a forecast takes 50 hours to run, it arrives after the decision has already been made. When a model requires 18 hours and still does not finish, the business defaults to gut instinct. HPC is the fix, and it is now accessible to companies without an in-house engineering department. Let us be precise about what HPC actually is. It distributes workloads across multiple coordinated computing resources, clusters, GPUs, cloud nodes, so that complex calculations run in parallel rather than in sequence. The cloud is not HPC. AI is not HPC. The cloud is a delivery model. AI is a type of workload. HPC is the engine underneath. Two cases from Electi's own work make this concrete. A retail client with 42 stores needed weekly demand forecasts across 8,600 SKUs, accounting for seasonality, promotions, and product cannibalization. On a single server, the full cycle took 50 hours. After migrating to a distributed architecture, it dropped to four hours. The team could now run the model before conditions changed, not after. In energy, a dataset of 14 million hourly consumption records, combined with weather, tariff, and production variables, required optimizing over 200 hyperparameter combinations across five algorithms. On a single machine with 32 GDB of RAM, the process stalled at 18 hours without finishing. On a cluster with 128 virtual CPUs and 512 GB of aggregate RAM, the pipeline completed in under three hours. The cost question is also worth addressing directly. For a typical SME dataset ranging from 5 to 50 million records, infrastructure costs run between 400 and 1200 euros per month. The most common mistake is overprovisioning, buying for the annual peak, and leaving most of that capacity idle the rest of the year. One data point that should concern any Italian SME. In 2024, only 5.7% of Italian companies with at least 10 employees reported using AI, against an EU average of 13.5%. That gap is not a cultural problem, it is a compute problem, and it is solvable. The skeptical question to ask is not whether HPC is powerful, it is whether your slowest analysis is costing you more than fixing it would. In most cases, it is. That's the review.