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  2. Tesla Autopilot hardware - Wikipedia

    en.wikipedia.org/wiki/Tesla_Autopilot_hardware

    With all eight cameras enabled, data extracted from Autopilot in debugging mode showed the cameras provide a black-and-white feed to the computer, possibly to improve image processing speed. [27] The Tesla Model 3, introduced in 2017, and related Model Y, introduced in 2019, are equipped with an additional driver-facing in-cabin camera.

  3. DeepSpeed - Wikipedia

    en.wikipedia.org/wiki/DeepSpeed

    Features include mixed precision training, single-GPU, multi-GPU, and multi-node training as well as custom model parallelism. The DeepSpeed source code is licensed under MIT License and available on GitHub. [5] The team claimed to achieve up to a 6.2x throughput improvement, 2.8x faster convergence, and 4.6x less communication. [6]

  4. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  5. Tesla (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Tesla_(microarchitecture)

    Tesla is the codename for a GPU microarchitecture developed by Nvidia, and released in 2006, as the successor to Curie microarchitecture. It was named after the pioneering electrical engineer Nikola Tesla .

  6. Tesla Dojo - Wikipedia

    en.wikipedia.org/wiki/Tesla_Dojo

    During a test, the company stated that Project Dojo drew 2.3 megawatts (MW) of power before tripping a local San Jose, California power substation. [18] At the time, Tesla was assembling one Training Tile per day. [10] In August 2023, Tesla powered on Dojo for production use as well as a new training cluster configured with 10,000 Nvidia H100 ...

  7. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Automatic differentiation [2] Has pretrained models Recurrent nets Convolutional nets RBM/DBNs Parallel execution (multi node) Actively developed BigDL: Jason Dai (Intel) 2016 Apache 2.0: Yes Apache Spark Scala Scala, Python No No Yes Yes Yes Yes Caffe: Berkeley Vision and Learning Center 2013 BSD: Yes Linux, macOS, Windows [3] C++: Python ...

  8. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    Tesla C1060, Tesla S1070, Tesla M1060 2.0 Fermi: GF100, GF110 GeForce GTX 590, GeForce GTX 580, GeForce GTX 570, GeForce GTX 480, GeForce GTX 470, GeForce GTX 465, GeForce GTX 480M Quadro 6000, Quadro 5000, Quadro 4000, Quadro 4000 for Mac, Quadro Plex 7000, Quadro 5010M, Quadro 5000M Tesla C2075, Tesla C2050/C2070, Tesla M2050/M2070/M2075 ...

  9. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    LongTensor {1, 2})-0.2381-0.3401-1.7844-0.2615 0.1411 1.6249 0.1708 0.8299 [torch. DoubleTensor of dimension 2 x4 ] > a : min () - 1.7844365427828 The torch package also simplifies object-oriented programming and serialization by providing various convenience functions which are used throughout its packages.