What Company Makes The Volta Chip For AI?

Volta AI image source Volta

Volta chip for AI  is made by Nvidia Corporation. This chip  uses the Nvidia volta architecture  and is designed for the artificial intelligence and as well as deep learning. It is a high-end chip capable of performing complex  computations and data analysis.

The Volta chip is based on Nvidia’s  volta architecture , which the company uses to develop its graphics processing unit (GPU). The architecture features Tensor Cores whose functions is to  execute the deep learning functionalities. The cores also accelerate  the training and inferencing of the neural networks.

Let’s discuss more about the Volta chip by Nvidia and the impact that it is making in the AI industry.

Features of Volta chip for AI

NVIDIA’s Volta chip features a high-performance architecture that is perfect for artificial intelligence, machine learning and other performance-oriented computing tasks. It comprises of a number of features that make it possible to achieve these goals. The key features of this AI chip include the following.

Tensor Cores

This is the most notable characteristic of the Volta AI by Nvidia. The main function of Tensor cores is to perform the matrix operations that are used for executing the deep learning algorithms. The cores have a capacity of delivering up to 125 teraflops  which are perfect for training the neural networks

Tensor cores on the Volta chip can work on the 4×4 matrices that are commonly found on the deep learning. These operates speed up the learning and training processes of the AI models.

The ability to perform mixed-precision calculations is another advantage of the Tensor cores. This type of calculation allows algorithms to use low-precision data types without affecting  the accuracy of the system. The use of low-precision data types is encouraged as it lowers the memory and power requirements by the algorithms.

Additionally, the fact that Tensor Cores are supported by numerous frameworks such as PyTorch and  TensorFlow makes them a perfect feature of Volta chip for AI.

High memory bandwidth

This is another key feature of the NIVIDIA’s Volta  chips. As expected, it is a must-have feature for any AI-based chip. Memory bandwidth  streamlines the issue of data management by an AI chip. It speeds up the rate of data transfer  between the storage, CPU and GPU.  The higher the bandwidth the better the system.

The Volta architecture from Nvidia features an ultra-high bandwidth system known as HBM2. This has the capacity of allowing the transfer rate of up to 900 GB/s. Also, the fact that HBM2  is stacked vertically optimizes the memory capacity of the chip whereby  it can store more within a small compact space.

The high memory bandwidth of the Volta architecture from Nvidia helps to improve the overall performance of an AI system. This mainly stems from the fact that memory management is directly related to the performance of a machine. It also reduces the time for the model training while at the same time guarantees the accuracy of a workload.

NVlink

The Volta is designed to support the NVLink. This is a high-speed technology that allows interconnection between multiple GPUs for efficient communication. These GPUs are able to relay data between each other without involving the CPU. It makes it possible to execute parallel processing, a key recipe required for the performance of most AI applications.

The end to end connection between the  CPUs and GPUs increases the data transfer rate and also eliminates the latency that always experienced in the traditional CPUs. It also expands the capacity of the Volta chip to handle large volumes of data at a time. The direct result of this when it comes to the field o AI is reduced training time for the models.

Scalability

Scalability is another desired feature of the AI chips. It refers to the ability to increase the handling and operational capacity of a chip when a need arises. The chip should be able to handle increased workloads or data without having negative impact on the performance.

Having more cores and higher bandwidth is just one of the ways in which the Volta chip for AI achieve scalability. This feature allows developers and other players involved to add more data and workload to the systems without worrying about the performance issues that may arise.

Does the Volta chip for AI from Nvidia have any software support?

In as much as AI chips are more focused on the hardware aspect of production, most AI applications require a blend of both software and software. The good news is NVIDIA has an array of libraries and tools that support AI applications under the Volta chips. These software  components include the following:

• CUDA Toolkit: CUDA is a parallel computing platform from Nvidia. The toolkit enables AI engineers to utilize the full power of the GPUs. CUDA encompasses tools and libraries for ML and deep leaning workloads.
• NVIDIA GPU Cloud(NGC): This is a cloud-based platform that gives developers unlimited access to a wide range of containers that are used for AI and ML. The containers also make it possible for the collaboration on different projects.
• Deep Learning Frameworks: Volta Chip from Nvidia provides full support for different machine learning and deep learning frameworks such as MXNet, TensorFlow and Pytorch.

So, in terms of support, we can say that Volta chip provides adequate support that is necessary for the growth and development of artificial intelligence. The chip is expected to have more software support over the years as the AI technology keeps growing.

Conclusion

Now you know the maker of Volta chip for AI-Nvidia. This is a big name in the chip  industry and has been making some serious inroads into the arena of artificial intelligence. However, keep in mind that volta does not refer to any specific type of chip. Instead, it is GPU architecture that has been implemented on different AI chips.

The future of Volta-based AI chips is promising and we expect more robust performance from these chips. If you are hoping to get into AI field, you should pa attention to this chip technology from Nvidia.

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