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Deep Learning

NVIDIA Deep Leanring

Deep Learning Hardware Solutions

Advances in computer technology has recently opened doors to the deep neural networks that was previously not obtainable. It enables machines to learn faster and helps them to become more accurate. It uses algorithms, big data, and the computational power of new age NVIDIA Tesla GPUs. Artificial Intelligence and AI Computing are being led by this technology and enabling human kind to achieve things that were never imagined before.

Deep Learning enables the research community and the industry to solve many real world problems with best accuracy. Image processing, speech recognition and translation, natural language processing, several driving assistance tools are being helped by deep learning in a way that was never acquired before. High-end GPUs and Server tools are being used in datacentres.

These advanced and high intensive computing algorithms takes current computing technology to their limits. Here at Workstation Specialists we offer a consultancy service and a range of solutions tailored to user’s needs. This allows users to rest assured that there investment is well spent on precisely what they require to achieve their goals.



New trends that is Revolutionizing Machine Learning

Machine Learning enables computers to learn from a huge bundle of data and they can self-correct programming pitfalls. When the machines are exposed to a large database, they can self-learn and evolve. Machine learning along with Artificial Intelligence is immensely powerful and it is assumable that this technology will lead the world in coming future.

Deep Learning is leading Machine Learning towards a better future. Speech recognition, Image processing, self-driven cars will lead the coming years with the help of High Performance Computing GPUs.

High-end NVIDIA Tesla GPUs like the newest edition of NVIDIA Tesla P100 processes massive computational power that will revolutionize the world of machine learning. Massive amount of data can be assessed in a small amount of time and it will enable advanced future technologies like self-driven cars and future climate prediction.

These GPUs are inherently amazing when it comes to managing parallel workloads and boosting the speed of the DNNs by ten to twenty times. This in turn further ensures that the training iterations take relatively lesser time. NVIDIA collaborated with some of the leading AI developers for improving their GPU design, their system architecture, codes and algorithms. They have also tweaked with the compilers for speeding up the training within the deep neural networks by fifty times in just three years. The company expects a further ten times boost in the next couple of years.

A future of AI driven smart apps, digital assistants and main stream use of Artificial Intelligence can be predicted from the advance of deep learning. The leap for a better future for human-kind will be assisted by high-end GPU and its exponentially increasing computational power.



NVIDIA Tesla Features and Benefits

The latest advances of NVIDIA Tesla technology now produces computation speed of hundreds of CPU server nodes. Datacentres of today can process large number of transactional workloads but it is not efficient for next generation scientific applications and artificial intelligence. Ultra efficient and lightning fast server nodes, is the specialty of NVIDIA Tesla.

Pascal Architecture Performance Boost-NVIDIA Tesla has recently rolled out its Pascal based P100 solution. This solution has accounted to a massive increase in the performance of the neural network trainings. This new Pascal architecture helps the Tesla P100 to offer the best and the highest possible performance for the HPC workloads. This works equally well with the hyper-scale workloads. With about 21 TeraFLOPs of FP16 performance, Pascal is specifically optimized for driving new openings and better possibilities in the applications of deep learning. At the same time, it also delivers about 5 to 10 TeraFLOPSs of single and double precision performance for handling and managing the HPC workloads.

Efficiency Boost with CoWoS with HBM2- The Pascal architecture combines the data and processor to an individual package which in turn delivers excellent compute efficiency. The memory design has been subject to an innovative approach via the chip on wafer on substrate (CoWos) with HBM2. This in turn, increases the memory three times more and boosts the performance of the bandwidth up to 720 GB/sec, when compared to the previous architecture of Maxwell. This further provides a significant generation leap in terms of time-to solutions for the various data-intensive apps.

Massive Scale Applications with NVIDIA NVLink – The performance of your existing systems is often affected by the, interconnects. This is exactly why the revolutionary NVIDIA NVLink has come to inception. The high speed and bi-directional GPU inter-connect from NVDIA NVLink works with the applications across several GPUs. This leads to a significant acceleration in the bandwidth speed (about 5X times) compared to the top notch solutions available today. Up to 8 NVIDIA Tesla P100 GPUs can be directly connected with NVLINK for maximizing the performance of the applications from on single node itself.

To add to this, the Tesla P100 GPU accelerator from NVIDIA offers an entirely new and innovative level of performance. It works exceptionally well with deep learning applications and HPC including the complex code for AMBER molecular dynamics. This code runs faster and better on an individual server node via the Tesla P100 GPUs when compared to the old 48-dual socket server nodes for CPU. Similarly, the deep neural network, Alexnet would take 250 dual-sockets of the conventional CPU server nodes to match up to the scalability of eight P100 GPUs from Tesla. The extensively used weather depicting application, COSMO too runs better and quicker on eight of Tesla P100 GPUs when compared to the performance with twenty seven dual sockets on the CPU servers.


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