Introduction to High-Performance Computing
1. From Room-Sized Machines to Life-Saving Simulations
Before diving into what High-Performance Computing (HPC) means today, let’s take a quick trip through time — from the machines that filled entire rooms to the systems that help us model the human brain, predict pandemics, and design new cancer drugs.
1940–1960s: The First Supercomputers
The birth of electronic computing
The first “supercomputers” emerged during World War II. They weren’t built for medicine, but for codebreaking, ballistics, and physics — yet they laid the foundation for every modern medical simulation.
🖥️ ENIAC (1945) — the first electronic general-purpose computer, built for U.S. Army ballistics.
These early machines were massive — the size of an operating room, consuming as much electricity as a hospital wing.
Their mission: calculate faster than any human could.
ENIAC (1945) — one of the first electronic supercomputers, programmed manually with cables and switches. Figure taken from Wikipedia.
1970–1990: The Cray Era
When speed became a race
In the 1970s, speed became the focus.
Supercomputers like the Cray-1 used vector processors to perform thousands of operations at once — a breakthrough that inspired modern GPUs (used in AI today).
“Cray-1 (1976) — elegant design and groundbreaking parallelism.”
(Original: Wikipedia – Cray-1)
1990–2010: The Cluster Era
From super-machines to super-teams of computers
Scientists realized that connecting many smaller computers could outperform one massive one — the birth of clusters.
1994: NASA engineers built the first Beowulf Cluster using standard PCs and Ethernet cables.
This democratized HPC — universities could now build their own “mini supercomputers.”
Photo of a Beowolf Cluster. Figure taken from https://memim.com/beowulf-cluster.html.
2010–Present: The GPU & Hybrid Era
From physics to AI and medicine
Today’s supercomputers combine traditional CPUs with GPUs and accelerators — the same hardware used for medical AI, radiology, and genomics.
Instead of a few super-fast processors, modern systems have thousands of smaller ones working together.
Modern HPC combines CPUs and GPUs for AI, simulations, and data analytics.
2. What Is HPC — and Why It Matters to You
So what exactly is HPC?
High-Performance Computing (HPC) means using many powerful computers at once to solve problems that are too big, too detailed, or too urgent for a single machine.
It’s the engine behind modern data-driven medicine — where algorithms, images, and molecules meet computation.
What is High-Performance Computing - YouTube (Croatian).
HPC in Everyday Healthcare Research
Here’s how HPC touches your field, even if you don’t see it directly:
Application |
HPC’s Role |
|---|---|
Radiology AI |
Train deep neural networks on thousands of MRI/CT scans. |
Drug discovery |
Simulate how molecules bind to proteins. |
Genomics |
Process hundreds of patient genomes in parallel. |
Epidemiology |
Model virus spread and hospital resource needs. |
Surgery planning |
Run 3D simulations of patient anatomy. |
3. Why Do We Need HPC?
Most modern medical and pharmaceutical challenges are too large for desktop computers:
A single CT scan can produce hundreds of megabytes of data.
One genome = 100 GB of raw data.
A deep learning model might require weeks of computation without HPC.
Laptop vs. Cluster
The Grand Challenges (and Opportunities)
The U.S. National Science Foundation once defined “Grand Challenges” — problems only solvable with HPC.
Many now directly relate to healthcare and life sciences:
Cancer detection and therapy
Drug design and molecular simulation
Climate and disease modeling
AI and deep learning
Understanding biological systems
In One Sentence:
🧠 HPC allows us to ask bigger questions — and get answers faster.
You can:
Solve bigger problems in the same time, or
Solve the same problems in less time.
Reflection
Where could HPC help you?
Think of a task in your daily work — an analysis, simulation, or AI model — that you wish could run faster or on more data.
Would HPC make it possible?