Parallel computingParallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.
Petascale computingPetascale 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.
Fugaku (supercomputer)Fugaku 富岳 is a petascale supercomputer at the Riken Center for Computational Science in Kobe, Japan. It started development in 2014 as the successor to the K computer and made its debut in 2020. It is named after an alternative name for Mount Fuji. It became the fastest supercomputer in the world in the June 2020 TOP500 list as well as becoming the first ARM architecture-based computer to achieve this. At this time it also achieved 1.42 exaFLOPS using the mixed fp16/fp64 precision HPL-AI benchmark.
Numerical methods for ordinary differential equationsNumerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals. Many differential equations cannot be solved exactly. For practical purposes, however – such as in engineering – a numeric approximation to the solution is often sufficient. The algorithms studied here can be used to compute such an approximation.
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.
Erasure codeIn coding theory, an erasure code is a forward error correction (FEC) code under the assumption of bit erasures (rather than bit errors), which transforms a message of k symbols into a longer message (code word) with n symbols such that the original message can be recovered from a subset of the n symbols. The fraction r = k/n is called the code rate. The fraction k’/k, where k’ denotes the number of symbols required for recovery, is called reception efficiency.
SupercomputerA supercomputer is a computer with a high level of performance as compared to a general-purpose computer. The performance of a supercomputer is commonly measured in floating-point operations per second (FLOPS) instead of million instructions per second (MIPS). Since 2017, there have existed supercomputers which can perform over 1017 FLOPS (a hundred quadrillion FLOPS, 100 petaFLOPS or 100 PFLOPS). For comparison, a desktop computer has performance in the range of hundreds of gigaFLOPS (1011) to tens of teraFLOPS (1013).
Data parallelismData parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel. It contrasts to task parallelism as another form of parallelism. A data parallel job on an array of n elements can be divided equally among all the processors.
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.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
