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Titan vs

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The NVIDIA Titan V is a high-performance graphics processing unit (GPU) designed for scientific and professional applications. It features the Volta architecture, which provides enhanced computational capabilities and improved energy efficiency compared to previous generations. The Titan V is optimized for accelerating workloads in areas such as artificial intelligence, scientific computing, and data analytics.

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Lab products found in correlation

Titan rtx gpu, by NVIDIA (2 mentions) Quadro p6000, by NVIDIA (2 mentions) Quadro m5000, by NVIDIA (2 mentions) Tesla v100, by NVIDIA (2 mentions) Geforce rtx 2080 ti, by NVIDIA (2 mentions)

2 protocols using titan vs

1

Fast.ai Deep Learning Protocol

Check if the same lab product or an alternative is used in the 5 most similar protocols
Final models were generated using fast.ai v1.0.55 library (https://github.com/fastai/fastai), PyTorch on two NVIDIA TITAN RTX GPUs. Initial experiments were conducted using NVIDIA Tesla V100s, NVIDIA Quadro P6000s, NVIDIA Quadro M5000s, NVIDIA Titan Vs, NVIDIA GeForce GTX 1080s, or NVIDIA GeForce RTX 2080Ti GPUs.
Fang L., Monroe F., Novak S.W., Kirk L., Schiavon C.R., Yu S.B., Zhang T., Wu M., Kastner K., Latif A.A., Lin Z., Shaw A., Kubota Y., Mendenhall J., Zhang Z., Pekkurnaz G., Harris K., Howard J, & Manor U. (2021). Deep Learning-Based Point-Scanning Super-Resolution Imaging. Nature methods, 18(4), 406-416.
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2

Fast.ai Deep Learning Protocol

Check if the same lab product or an alternative is used in the 5 most similar protocols
Final models were generated using fast.ai v1.0.55 library (https://github.com/fastai/fastai), PyTorch on two NVIDIA TITAN RTX GPUs. Initial experiments were conducted using NVIDIA Tesla V100s, NVIDIA Quadro P6000s, NVIDIA Quadro M5000s, NVIDIA Titan Vs, NVIDIA GeForce GTX 1080s, or NVIDIA GeForce RTX 2080Ti GPUs.
Fang L., Monroe F., Novak S.W., Kirk L., Schiavon C.R., Yu S.B., Zhang T., Wu M., Kastner K., Latif A.A., Lin Z., Shaw A., Kubota Y., Mendenhall J., Zhang Z., Pekkurnaz G., Harris K., Howard J, & Manor U. (2021). Deep Learning-Based Point-Scanning Super-Resolution Imaging. Nature methods, 18(4), 406-416.
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