One Exciting Advance in the Computer Industry
One of the most exciting advances happening in the computer industry recently has been the dramatic proliferation of GPU Computing into different kinds of solutions. The GPUs in crypto-currency mining is getting a lot of press lately. Full disclosure here, I have an 8x GPU rig as a test system. Also, GPUs are finding more uses in solving complex problems. Initially, GPUs were focused on graphics processing, and computer gaming experienced a renaissance in complexity, realism, and diversity. The corporate data center workloads were not able to take advantage of this tremendous increase in GPU computing power. As data volumes grew, the amount of traditional CPU power to process this data has not kept up. There became a problem of how to throw enough computing resources at a problem. All while not purchasing a “supercomputer” for millions of dollars.
The emergence of big data processing approaches, like Hadoop, has given data scientists a platform for storing and analyzing hundreds of TB of data on cheap, commodity hardware. This approach worked for a while. Companies could place tens to hundreds of small servers breaking up the work into their already employed datacenters. But there’s another shift coming that is causing data to grow at an even faster rate. That’s data generated by connected machines.
So, what does this have to do with GPU Computing?
The math these devices are designed to accomplish in processing high definition graphics is also REALLY good at plowing through machine-generated data. While a lot of attention has been paid to Machine Learning, Artificial Intelligence, and Crypto-Mining, GPUs are working their way further into the enterprise datacenter. Recently, Kubernetes and Spark have gained support for GPUs. Also, database applications like SQream are making GPU computing a reality for more general data analysis. For example, this data growth is happening so fast that NVIDIA’s data center business grew from $338M in 2016 to $830M in 2017. A perfect fit for Axellio MicroDatacenter.
The Axellio MicroDatacenter Platform is a next-generation architecture. It is designed for ultra high-performance components like GPUs and NVMe storage devices. FabricXpress™, a high bandwidth PCIe fabric, in Axellio can be customized for the GPU computing and storage needs of any environment. Combining high-performance storage devices (NVMe), TBs of RAM, dozens of CPU cores, and the power of multiple GPUs in a simple 2u architecture offers a flexibility that is purpose-built to process huge volumes of data at the edge of the network. SQream leverages this high-performance data architecture. It provides the fastest data analytics available on massive data stores.
We’ve recently completed testing with SQream’s GPU accelerated database, and the results were outstanding. Review the latest solution sheet between SQream DB & Axellio on how GPUs can accelerate your big data analytics projects. Or discuss your upcoming project by contacting us!