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Titan V vs Tesla P40

The Comparative Analysis of the Titan V and Tesla P40 on AI Algorithms

Many graphics cards, which are needed to solve the most demanding tasks in different areas, are released frequently. We have purchased a new graphics card – the Titan V and decided to compare it with the Tesla P40. Experiments on the performance of graphics cards were conducted. On the basis of the data obtained from experiments, we were able to find out which one is better. Let’s consider the characteristics of these video cards and the results of experiments.

Titan V and Tesla P40: Specifications

The NVIDIA Titan V according to the manufacturer, is the most powerful graphics card ever created for the PC, driven by the world’s most advanced architecture—NVIDIA Volta. This graphics card delivers new levels of performance. Built on the 12 nm process, and based on the GV100 graphics processor, in its GV100-400-A1 variant.

The NVIDIA Tesla P40 was designed to meet the challenges of the modern data center. This is a professional graphics card, built on the 16 nm process, and based on the GP102 graphics processor, in its GP102 variant.

Here is a comparison table.

General specs
GPU Titan V Tesla P40
Architecture Volta Pascal
GPU name GV100 GP102
Type Desktop Workstation
Release date December 7, 2017 September 13, 2016
Technical specs
Pipelines 5120 3840
Core clock speed 1200 MHz 1303 MHz
Boost Clock 1455 MHz 1531 MHz
Transistor count 21,100 million 12,000 million
Manufacturing process technology 12 nm 16 nm
Power consumption (TDP) 250 Watt 250 Watt
Texture fill rate 465.6 367.4
Floating-point performance 14,899 gflops 11,758 gflops
Thermal Threshold 91° C 45° C
Memory specs
Memory type HBM2 GDDR5X
Maximum RAM amount 12 GB 24 GB
Memory bus width 3072 Bit 384 Bit
Memory clock speed 1700 MHz 10008 MHz
Memory bandwidth 652.8 GB/s 480.4 GB/s
Board design
Slot Width Dual-slot Dual-slot
Length 10.5 inches 267 mm 10.5 inches 267 mm
Outputs 1x HDMI
3x DisplayPort
1x DVI
4x DisplayPort
Power Connectors 1x 6-pin + 1x 8-pin 1x 6-pin + 1x 8-pin


Titan V and Tesla P40: Results of Experiments

Architecture Experiment Results Note
Convolutional Neural Network. This model uses three convolutional layers and two fully connected layers 2000 iterations of training on the MNIST dataset It took 7 seconds the Titan V and 120 seconds the Tesla P40 to complete the experiment The fact that the Tesla P40 loaded the model approximately in a minute, whereas its counterpart did it almost instantly, influenced the results of the experiment
GAN uses two fully connected layers in the generator/discriminator 100,000 iterations of training on the MNIST dataset It took 183 seconds the Titan V and 519 seconds the Tesla P40 to complete the experiment The Titan V operated at its full capacity, and it loaded the information for processing faster than the Tesla P40
DCGAN uses approximately three convolutional layers in the generator and discriminator, that is why this model is more complex than GAN 20,000 iterations of training on the MNIST dataset It took 96 seconds the Titan V and 308 seconds the Tesla P40 to complete the experiment The Titan V operated at its full capacity, and it loaded the information for processing faster than the Tesla P40
ResNet is one of the largest neural networks, which is often used to transfer the learning experience from one large dataset to another one, which is smaller and more specialized. ResNet uses thirty-two convolutional layers, plus several fully connected layers 10,000 iterations of training on the cifar10 dataset It took 151 seconds the Titan V and 420 seconds the Tesla P40 to complete the experiment  
WideNet takes a huge input from statistics, not the image 10,000 iterations of training on the tax statistics dataset  It took 12 seconds the Titan V and 57 seconds the Tesla P40 to complete the experiment  

Thus, considering all the above, we can conclude that the Titan V has better characteristics than the Tesla P40. So, the Titan V is much newer (7 December 2017 vs 13 September 2016), it has a wider memory bus (3072 vs 384 bit), more pipelines (5120 vs 3840), a higher memory bandwidth (652.8 vs 480.4 GB/s), and a finer manufacturing process technology (12 vs 16 nm). Based on the results of experiments, conducted on different models (Convolutional Neural Network, GAN, DCGAN, ResNet, WideNet), we can assert that the Titan V video card is more powerful than the Tesla P40.

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