Top 500 Supercomputers

China's rapid growth as an economic power is reflected in its compound growth in computing performance. While the United States retains a comfortable lead, China has rapidly risen to second place in overall compute power. In two years it has increased its average rank by 100 positions, and now runs the most powerful computing cluster.

Robert Morton, Tableau Database Engineer Extraordinaire, sent us this viz. Explore it view below (and click through the tabs!) to get a more detailed view.

China's rapid growth as an economic power is reflected in its compound growth in computing performance. While the United States retains a comfortable lead, China has rapidly risen to second place in overall compute power. In two years it has increased its average rank by 100 positions, and now runs the most powerful computing cluster.

Robert Morton, Tableau Database Engineer Extraordinaire, sent us this viz. Explore it view below (and click through the tabs!) to get a more detailed view.

China's Growth

Supercomputing resources are used in very different fashions by each country. This dashboard gives an overview of the size and type of each county's supercomputing clusters, and shows how each country has ranked in this list over more than a decade. China has clearly dominated the growth curve, but the United States still holds a commanding lead over total capacity.

Top 500 Around the World

Supercomputing resources are used in very different fashions by each country. This dashboard gives an overview of the size and type of each county's supercomputing clusters, and shows how each country has ranked in this list over more than a decade. One of the most important things shown in this view is the contrast between industry-centric China and research-based Japan.

Moore's Law

Moore's Law observes that a microprocessor's transistor count has doubled roughly every two years. Prior to this decade, increasing transistor density correlated with increasing processor frequency. Recently however performance has scaled mostly with parallelism, and we see that processor frequency remains stable while performance per core shows only modest gains.

Increasing the core count of a computing cluster has become the most effective means of increasing computing power. This has driven substantial innovation in networking / interconnect technology, which has kept the per-core computing efficiency relatively stable.