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In September 2022 Nvidia announced the Jetson Orin Nano. [ 14 ] [ 15 ] The modules have the same 260-pin SO-DIMM connector and 69.6 mm x 45 mm dimensions, and come in two variants. The 4 GB variant provides 20 Sparse or 10 Dense TOPs, using a 512-core Ampere GPU with 16 Tensor cores, while the 8 GB variant doubles those numbers to 40/20 TOPs, a ...
Nvidia Jetson Orin Nano [171] low-power, cost-effective SODIMM-form factor Orin-series module, available as standalone module or devkit; intended for entry-level usage Unknown Nio Adam [172] [173] built from 4x Nvidia Drive Orin, totals to 48 CPU cores and 8,192 CUDA cores; for use in vehicles ET7 in March 2022 and ET5 in September 2022 T239 ...
Arduino Nano [32] Arduino Yes ATmega328 [27] (ATmega168 before v3.0 [33]) 16 MHz minimal 1.70 in × 0.73 in [ 43.18 mm × 18.54 mm ] USB FTDI FT232R [34] 5 V 16/32 0.5/1 1/2 14 6 8 May 15, 2008 [35] This small USB-powered version of the Arduino uses a surface-mounted processor. LilyPad Arduino [36] Arduino Yes ATmega168V or ATmega328V 8 MHz ...
Arduino form factor compatible ARM Cortex-M3 Development Platform: 24-bit data acquisition system that incorporates dual high performance, multichannel sigma-delta (Σ-Δ) analog-to-digital converters (ADCs), a 32-bit ARM Cortex™-M3 processor, and flash/EEPROM memory on a single chip.
Nvidia Drive is a computer platform by Nvidia, aimed at providing autonomous car and driver assistance functionality powered by deep learning. [1] [2] The platform was introduced at the Consumer Electronics Show (CES) in Las Vegas in January 2015. [3]
In computing, computer performance is the amount of useful work accomplished by a computer system. Outside of specific contexts, computer performance is estimated in terms of accuracy, efficiency and speed of executing computer program instructions. When it comes to high computer performance, one or more of the following factors might be involved:
The Nano [1] microprocessor from VIA Technologies is an eighth-generation CPU targeted at the consumer and embedded market. Desktop and mobile processors
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.