Exascale computingExascale 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 GeneBlue 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 magnitudeThis 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.
TOP500The TOP500 project ranks and details the 500 most powerful non-distributed computer systems in the world. The project was started in 1993 and publishes an updated list of the supercomputers twice a year. The first of these updates always coincides with the International Supercomputing Conference in June, and the second is presented at the ACM/IEEE Supercomputing Conference in November.
Folding@homeFolding@home (FAH or F@h) is a distributed computing project aimed to help scientists develop new therapeutics for a variety of diseases by the means of simulating protein dynamics. This includes the process of protein folding and the movements of proteins, and is reliant on simulations run on volunteers' personal computers. Folding@home is currently based at the University of Pennsylvania and led by Greg Bowman, a former student of Vijay Pande.
