Google’s Cloud Platform is the relative newcomer on the public cloud block, and has a way to go before before it is in the same competitive sphere as Amazon Web Services and Microsoft Azure, both of which deliver a broader and deeper range of offerings and larger infrastructures. …
As a thought exercise, let’s consider neural networks as massive graphs and begin considering the CPU as a passive slave to some higher order processor—one that can sling itself across multiple points on an ever-expanding network of connections feeding into itself, training, inferencing, and splitting off into multiple models on the same architecture. …
The need for speed to process neural networks is far less a matter of processor capabilities and much more a function of memory bandwidth. …
A shared appetite for high performance computing hardware and frameworks is pushing both supercomputing and deep learning into the same territory. …
Just five years ago, the infrastructure space was awash in stories about the capabilities cooked into the Hadoop platform—something that was, even then, only a few pieces of code cobbled onto the core HDFS distributed storage with MapReduce serving as the processing engine for analytics at scale. …
The idea of bringing compute and memory functions in computers closer together physically within the systems to accelerate the processing of data is not a new one. …
During the past decade, enterprises have begun using machine learning (ML) to collect and analyze large amounts of data to obtain a competitive advantage. …
When it comes to solving deep learning cluster and software stack problems at scale, few companies are riding the bleeding edge like Chinese search giant, Baidu. …
Five years ago, many bleeding edge IT shops had either implemented a Hadoop cluster for production use or at least had a cluster set aside to explore the mysteries of MapReduce and the HDFS storage system. …
Much of the talk around artificial intelligence these days focuses on software efforts – various algorithms and neural networks – and such hardware devices as custom ASICs for those neural networks and chips like GPUs and FPGAs that can help the development of reprogrammable systems. …
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