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2×10 15: Nvidia DGX-2 a 2 Petaflop Machine Learning system (the newer DGX A100 has 5 Petaflop performance) 11.5×10 15: Google TPU pod containing 64 second-generation TPUs, May 2017 [9] 17.17×10 15: IBM Sequoia's LINPACK performance, June 2013 [10] 20×10 15: roughly the hardware-equivalent of the human brain according to Ray Kurzweil.
A minicomputer, or colloquially mini, is a type of general-purpose computer mostly developed from the mid-1960s, [1] [2] built significantly smaller and sold at a much lower price than mainframe [3] and mid-size computers from IBM and its direct competitors. By 21st century-standards however, a mini is an exceptionally large machine ...
A mini PC (or miniature PC, nettop, or Smart Micro PC) is a small-sized, inexpensive [1], low-power, [2] [3] legacy-free desktop computer designed for basic tasks such as web browsing, accessing web-based applications, document processing, and audio/video playback. [4] [5] [6] The word nettop is a portmanteau of network and desktop.
A Google Tensor Processing Unit v4 pod is capable of 1.1 exaflops of peak performance, [98] while TPU v5p claims over 4 exaflops in Bfloat16 floating-point format, [99] however these units are highly specialized to run machine learning workloads and the TOP500 measures a specific benchmark algorithm using a specific numeric precision.
A supercomputer is focused on performing tasks involving intense numerical calculations such as weather forecasting, fluid dynamics, nuclear simulations, theoretical astrophysics, and complex scientific computations. A supercomputer is a computer that is at the front-line of current processing capacity, particularly speed of calculation.
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The appearance of even lower-priced scientific workstations (e.g., Dana Computer/Ardent Computer/Stellar Computer (the merger of these companies)) based on microprocessors with high performance floating point units (FPUs) during the 1990s (such as the MIPS R8000, IBM POWER2), and Weitek eroded the demand for this class of computer.