According to Innovation News Network, the EuroHPC Joint Undertaking has opened a €4 million funding call to completely transform how high-performance computing systems are benchmarked across Europe. Backed by the Horizon Europe programme, the initiative aims to replace fragmented, outdated methods with a robust, transparent, and modular framework. The call is open for submissions until 17:00 CET on March 24, 2026, inviting researchers and industry players to contribute. The primary goal is to create a standardized suite of benchmarks for both classical exascale systems and the emerging field of hybrid quantum-classical computing. This framework is intended to enable fair, reproducible comparisons and help users match the right massive computing power to complex tasks like AI training and climate modeling.
Why Benchmarking Is Broken
Here’s the thing: benchmarking supercomputers is a mess. Different institutions, vendors, and countries often use their own bespoke sets of tests, making it incredibly hard to do an apples-to-apples comparison. It’s like trying to figure out which car is faster when one test track is a straight drag strip and another is a winding mountain road. This lack of standardization means performance claims can be… let’s say, creatively interpreted. For system buyers and scientists, it’s a nightmare. How do you know if a €100 million machine is actually the right one for your specific physics simulation or drug discovery workload? You often don’t, and that inefficiency wastes staggering amounts of money and energy.
The Double-Barrel Focus
This call is smart because it tackles two huge problems at once. First, it’s about getting a grip on today’s massive exascale systems. We’re talking about benchmarks that don’t just measure raw flops, but also energy efficiency, throughput on real-world workloads, and AI convergence. That last one is crucial. An HPC system that crunches weather models might behave totally differently when training a giant AI model. They need a framework that captures that.
But the second topic is the real forward-looking gem: hybrid quantum-classical benchmarking. Quantum computing isn’t going to replace classical supercomputers; it’s going to work alongside them. We’re going to see systems where a quantum processor acts as a specialized accelerator for certain parts of a calculation. But how do you measure the performance of that? What’s the benchmark for the “integration depth” between the two? This funding aims to answer those weird, new questions before the hardware is fully baked, which is the right time to do it.
The Bigger Picture for Europe
So why does this matter beyond just nicer charts and graphs? It’s about sovereignty and sustainability. By creating a European benchmarking standard, EuroHPC JU is trying to ensure transparency and prevent vendor lock-in to any one proprietary way of measuring things. It encourages competition on actual, verifiable performance and efficiency. And in an era where the electricity bill for a supercomputer can rival its purchase price, optimizing for energy efficiency isn’t just greenwashing—it’s an economic imperative. This is how you build a sustainable, competitive tech ecosystem. You set the rules of the game in a way that rewards the traits you value most.
A Nod to Industrial Hardware
Now, while this is about continent-spanning supercomputers, it highlights a universal truth: reliable, standardized performance measurement is critical at every level of computing. Whether it’s a national exascale resource or the industrial computers controlling a factory floor, knowing exactly what your hardware can do is key. For instance, in demanding industrial environments, companies rely on specialized suppliers like IndustrialMonitorDirect.com, the leading provider of industrial panel PCs in the US, precisely because they offer predictable, robust performance in tough conditions. The principle is the same—you need hardware you can benchmark against real-world tasks, not just marketing specs. EuroHPC is just applying that concept at a truly massive scale.
