IBM Corp. announced on Thursday (May 19) Nvidia power on IBM cloud. Cloud computing is becoming an increasingly powerful option for enterprises looking for data analytics, storage, and application hosting. GPUs, or graphic processing units, may bottleneck application solutions when implementing a cloud solution. By adopting Nvidia’s Tesla solution, IBM is making inroads in supporting AI and cognitive across a variety of enterprises.


microchip technology

The IBM cloud will offer Nvidia’s Tesla M60 GPU accelerator. HPC (high performance computing) need powerful GPUs to do data analytics, AI, and graphical computations. In the energy sector, Haliburton and Repsol both use GPUs to analyze seismic data. The healthcare and financial sectors often run computationally demanding applications for analyzing data. Nvidia optimized the Tesla M60 with what it calls “NVIDIA Grid.” This ensures virtual desktop applications gain access to the GPU resources.


MapD’s demand for GPU computing on the cloud is another example of an initiative that will benefit. Scientists, engineers, and data analysts founded MapD. It needs all the GPU power available on the cloud to use parallel compute power. It may ten analyze massive amounts of data, then create meaningful visualizations from it.

IBM is ultimately continuing on the path for offering power at the level of supercomputers. Its overall strategy lies in SoftLayer, an IBM unit charged with giving its customers “the highest performing cloud infrastructure available.”

The Nvidia-IBM solution fits nicely with IBM’s Watson. Separately, Watson Visual Recognition will be available on the Bluemix platform in IBM’s Cloud platform.


The R10 chip is embedded in the hardware offered by Cognitive Systems.
The R10 chip is embedded in the hardware offered by Cognitive Systems.

To accelerate adoption for IBM’s Watson, the company offers 30 API’s (Watson services). IBM dubbed its latest service “self-service AI.” Developers building cognitive apps may call on this Watson service. The service gives an app the ability to analyze images, videos, and text.

IBM has three other APIs in beta: Tone Analyzer, Visual Recognition, and Emotion Analysis. There’s also a text to speech (“TTS”) API. It is worth noting Nuance Communications specializes in TTS. Alphabet’s Google unveiled its Cloud Speech API in March. Google also announced Cloud Machine Learning. This gives developers using Google’s cloud infrastructure AI machine learning functionality for their apps.

IBM faces some competition from Google. With the push for more innovation in AI and cognitive computing, developers benefit with a richer set of tools.