Baidu Targets Deep Learning Scalability Challenges
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. …
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. …
Whether being built for capacity or capability, the conventional wisdom about memory provisioning on the world’s fastest systems is changing quickly. …
Many oil and gas exploration shops have invested many years and many more millions of dollars into homegrown codes, which is critical internally (competitiveness, specialization, etc.) …
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. …
Despite the emphasis on X86 clusters, large public clouds, accelerators for commodity systems, and the rise of open source analytics tools, there is a very large base of transactional processing and analysis that happens far from this landscape. …
Like all hardware device makers eager to meet the newest market opportunity, Intel is placing multiple bets on the future of machine learning hardware. …
More than almost any other market or research segment, genomics is vastly outpacing Moore’s Law. …
We have written much about large-scale deep learning implementations over the last couple of years, but one question that is being posed with increasing frequency is how these workloads (training in particular) will scale to many nodes. …
Being at the bleeding edge of computing in the life sciences does not always mean operating at extreme scale. …
In distributed computing, there are two choices: move the data to the computation or move the computation to the data. …
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