Petascale computing

Petascale computing refers to computing systems capable of calculating at least 1015 floating point operations per second (1 petaFLOPS). Petascale computing allowed faster processing of traditional supercomputer applications. The first system to reach this milestone was the IBM Roadrunner in 2008. Petascale supercomputers were succeeded by exascale computers. Floating point operations per second (FLOPS) are one measure of computer performance. FLOPS can be recorded in different measures of precision, however the standard measure (used by the TOP500 supercomputer list) uses 64 bit (double-precision floating-point format) operations per second using the High Performance LINPACK (HPLinpack) benchmark. The metric typically refers to single computing systems, although can be used to measure distributed computing systems for comparison. It can be noted that there are alternative precision measures using the LINPACK benchmarks which are not part of the standard metric/definition. It has been recognised that HPLinpack may not be a good general measure of supercomputer utility in real world application, however it is the common standard for performance measurement. The petaFLOPS barrier was first broken on 16 September 2007 by the distributed computing Folding@home project. The first single petascale system, the Roadrunner, entered operation in 2008. The Roadrunner, built by IBM, had a sustained performance of 1.026 petaFLOPS. The Jaguar became the second computer to break the petaFLOPS milestone, later in 2008, and reached a performance of 1.759 petaFLOPS after a 2009 update. By 2018, Summit had become the world's most powerful supercomputer, at 200 petaFLOPS before Fugaku reached 415 petaFLOPS in June 2020.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (9)

Related people (1)

Related units (4)

Related concepts (7)

Related courses (1)

Related lectures (11)

COM-490: Large-scale data science for real-world data

This hands-on course teaches the tools & methods used by data scientists, from researching solutions to scaling up prototypes to Spark clusters. It exposes the students to the entire data science pipe

Numerical simulations are of a tremendous help to understand the growth of non-linear cosmological structures and how they lead to the formation of galaxies. In recent years, with the goal of improving their prediction power, new hydrodynamical techniques ...

EPFL2021

, , ,

Quantum ESPRESSO is an open-source distribution of computer codes for quantum-mechanical materials modeling, based on density-functional theory, pseudopotentials, and plane waves, and renowned for its performance on a wide range of hardware architectures, ...

AMER INST PHYSICS2020

Predictive Reliability and Fault Management in Exascale Systems

David Atienza Alonso, Marina Zapater Sancho

Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the ...

2020

Exascale computing

Exascale computing refers to computing systems capable of calculating at least "1018 IEEE 754 Double Precision (64-bit) operations (multiplications and/or additions) per second (exaFLOPS)"; it is a measure of supercomputer performance. Exascale computing is a significant achievement in computer engineering: primarily, it allows improved scientific applications and better prediction accuracy in domains such as weather forecasting, climate modeling and personalised medicine.

IBM Blue Gene

Blue Gene is an IBM project aimed at designing supercomputers that can reach operating speeds in the petaFLOPS (PFLOPS) range, with low power consumption. The project created three generations of supercomputers, Blue Gene/L, Blue Gene/P, and Blue Gene/Q. During their deployment, Blue Gene systems often led the TOP500 and Green500 rankings of the most powerful and most power-efficient supercomputers, respectively. Blue Gene systems have also consistently scored top positions in the Graph500 list.

Computer performance by orders of magnitude

This list compares various amounts of computing power in instructions per second organized by order of magnitude in FLOPS. Scientific E notation index: 2 | 3 | 6 | 9 | 12 | 15 | 18 | 21 | 24 | >24 TOC 5×10−1: Computing power of the average human mental calculation for multiplication using pen and paper 1 OP/S: Power of an average human performing calculations using pen and paper 1 OP/S: Computing power of Zuse Z1 5 OP/S: World record for addition set 5×101: Upper end of serialized human perception computation (light bulbs do not flicker to the human observer) 2.

Superconducting Digital Electronics: Advantages and Challenges MSE-438: Superconducting electronics: A materials perspective

Explores superconducting digital electronics, focusing on speed, power consumption, and historical developments in Cryotron and Josephson logic.

Internet of Things: Enabling Technology and Future Applications

Explores the evolution and impact of the Internet of Things, discussing the potential of technology in revolutionizing various sectors and emphasizing the importance of collaboration between developers and medical professionals.

Computational Study of Quantum Interaction Phenomena

Delves into computational quantum interaction phenomena in materials using high-performance computing, covering N-particle quantum mechanics, ab initio approaches, and the NOMAD Center of Excellence.