Supercomputers are gaining fast momentum as super computing prices are dropping.

There are already an increasing need for powerful computer systems for consumer analysis, science, innovation, and other business models. Here a supercomputer comes in with or above the latest highest running time. In floating-point operations per second, supercomputers’ efficiency is usually calculated (FLOPS), rather than millions of instructions per second (MIPS).  Here below is a list of the world’s ten best supercomputers for super computing.

1. FugakuFuga: RIKEN and Fujitsu co-developed Fugaku, The supercomputer designed with the Fujitsu A64FX microprocessor was named after an alternate term for Mount Fuji. The Scalable Vector Extensions for Supercomputers is based on the 8.2A processor design of the ARM version. The Fugaku plant in Kobe, Japan, is designed for applications that deal with high-priority social and research problems at the RIKEN Centre for Computational Science (R-CCS). It involves low power usage, strong computational efficiency, user comfort, and the capacity to achieve ground-breaking results, 30 to 40 MW energy consumption, and architecture that is ideal for AI applications like deep learning.
2. Sierra: The Lawrence Livermore National Laboratory for use as the second Integrated Technology Device by the National Nuclear Safety Administration (NNSA), Sierra, is one of the world’s largest supercomputers. The framework offers computing capabilities essential for nuclear weapons scientists to carry out the NNSA’s storage task by simulating rather than measuring underground. The IBM-built Sierra Special Machine accomplishes sustainable throughput efficiency six times and more than five times sustainable scientific efficiencies, Sequoia’s 125 PetaFLOP/s limits. This supercomputer, which links the IBM Power 9 processors and Volta graphics processing units from NVIDIA, has a power consumption of around 11MW, five-fold higher than Sequoia.
3. TaihuLight Sunway: Sunway TaihuLight, China’s supercomputer with the LINPACK benchmark rate of 93 petaflops, has been rated third in the TOP500 chart since November 2018. The supercomputer uses 40,960 RISC processors, which are built in China, based on Sunway architecture, with a total of 64-bit RISC processors. Every processor chip has 256 processing cores and four additional axes (also more completely loaded RISC cores) for the whole device for a total of 10,649,600 CPU cores. The SW26010 CPU, the Shanghai High-performance IC Concept Center chip, is the device that operates the Linux Sunway Raise OS 2.0.5.
4. HPC5: Since 2018 (HPC4), the overall computer infrastructure capability is 70 petaFlops: 70 billion mathematical operations in a single second by the operating super computing framework. HPC5 is the most efficient industrial supercomputer globally, housed within Eni’s Green Data Center with a peak capacity of over 50 Petaflops.
5. Tianhe-2: Tianhe-2, a supercomputer built by the Chinese National Defense Technology, University that processes 33.9 petaflops, almost two times the Titan or Sequoia performance, and over ten times the Tianhe-1A performance. Tianhe-2 will be used for training and testing, based at the National Super Computer Center in Guangzhou. It also runs a custom edition of the Ubuntu Linux operating system, known as Kylin, developed through a collaboration with the NUDT, China Software and CSIP, and Canonical (Ubuntu Creators).
6. Marconi-100: This provides almost 32 theoretical petaFLOPs of computational resources or estimates of up to 32 quadrillions per second. Via the PRACE project, and through Italian researchers through the Italian Resource Allocation (ISCRA) initiative, Marconi100 will help European researchers. This will allow them to address climate change’s societal challenges, clean energies, sustainable economics, and precision medicine by offering additional machine tools.
7. Summit: the IBM SuperComputer Summit can be 200 petaFLOPS to be the largest supercomputer worldwide, planned for use in the Oak Ridge National Laboratory. Its latest LINPACK benchmark is 148.6 petaFLOPS. The Summit provides science researchers with immense computational resources to address historically impossible problems in the fields of oil, IA, public health, and other science. These results would undeniably lead to worldwide human awareness, improve US global competitiveness, and contribute to a prosperous future.
8. Piz Daint: the Swiss NSC supercomputer, Piz Daint, has a computational potential of 7.8 petaFlops, indicating 7.8 quadrillions per second of a mathematical function. This supercomputer is capable of computing a new laptop in 900 years, in one day. Piz Daint is a Cray XC30 28 cabinet with an overall measurement node of 5’272. The computing nodes include an 8-core Intel Sandy Bridge CPU (Intel® Xeon® E5-2670), a 6 GB of GDDR5, and 32 Go of the host memory of the NVIDIA® Tesla® K20X. The nodes are linked to a dragonfly network topology through Cray’s patented “Aries” connection.
9. Trinity: The Trinity Supercomputer seeks to provide the NNSA Nuclear Security Enterprise with an expanded computing capacity to assist with continuously daunting activities. The supercomputer’s capability for promoting NNSA’s certification and tests for the nation’s nuclear arsenal must be handled and controlled by the Los Alamos National Laboratory and Sandia National Laboratories, under the Extreme-Scale Computing Alliance (ACES), to ensure stable, efficient, and secure nuclear storage. The Trinity was developed over 2 phases – the first phase was designed with the Intel Xeon Haswell processor. The other phase with the Intel Xeon Phi Knights Landing Processor incorporated substantial output increments.
10. Frontera: Frontera is Austin’s fastest academic supercomputer at Texas University. The Processing Resources have two subsystems: the main device that concentrates on dual-precision output and a second subsystem that focuses on single-precision streaming memory. Furthermore, Frontera has many database facilities, cloud and archive interfaces, and a range of application nodes for running virtual servers.

Conclusion: These machines consist of thousands of parallel processors, which satisfy the growing needs to process thousands of data with consistency and accuracy inreal-time.