Cavium has launched its latest ARM server processor, the ThunderX2, a second-generation SoC aimed at the same datacenter workloads that are currently dominated by Intel’s Xeon CPUs. The new chip is designed to go head-to-head with those Xeons, while at the same time get out in front of the 64-bit ARM competition from Applied Micro, Broadcom, and others.
The fourth industrial revolution is upon us. At least that’s the view of German business leaders and the government, who are blazing a new path in manufacturing with the Industrie 4.0 initiative. As in the third industrial revolution, information technology will be key enabler. But what comes next will intimately link manufacturing with the internet, the ubiquitous digital platform of the 21st century, along with other advanced computer technologies. The result will be what is sometimes referred to as the smart factory.
Google isn’t the only hyperscale company that is developing autonomous vehicles. Chinese internet giant Baidu is also aggressively pursuing this nascent market, albeit with less public fanfare than its American counterpart. This week though, more about the project’s inner workings was revealed when Inspur announced that its GPU-accelerated servers had been selected by Baidu as a platform for the company’s deep learning image recognition system.
If you happen to think there aren’t enough interconnect standards for accelerators in the world, then you’ll be happy to know that one more has been added to the heap. The new technology, known as the Cache Coherent Interconnect for Acceleration (CCIX), is being crafted as an open standard and aims to provide a high performance, cache coherent data link between processor hosts and coprocessor accelerators.
Last week at the Google I/O conference, it was revealed the search giant has been using its own custom-built ASIC to accelerate the machine learning capabilities that now underlies much of the Google cloud. The microprocessor, known as the Tensor Processing Unit (TPU), was designed by Google engineers to speed up the TensorFlow software that the company uses to drive much of its machine learning functionality. TensorFlow began as a machine learning research project, but later moved into production, and is now deployed in an array of applications, including Google Cloud Speech, Gmail, Google Photos, and Search. According to the company, TPUs have been churning away in their production datacenters for about a year, unbeknownst to its users.
Supercomputer-maker Cray has introduced Urika-GX, the company’s newest version of its enterprise-focused data analytics product line. With an emphasis on agility, the system merges the functionality of the existing Urika-GD and Urika-XA appliances, which provide platforms for graph-based and Spark/Hadoop-based analytics, respectively. Urika-GX wraps both of these capabilites into a single box, and does so largely with standard hardware and software.
The Times of India is reporting that the country will begin building a new series of domestically produced supercomputers, the first of which will be installed in August of 2017. The Rs 4,500-crore (about $670 million) project is being managed by the Centre for Development of Advanced Computing (C-DAC).