Machine learning is advancing in a broad range. Here are a few applications proposed today (listed without any particular order):
For over thirty years, “RAID” configurations have been widely used throughout the IT-sphere to improve the reliability and performance of storage solutions. This technology’s lifespan demonstrates its usefulness, long before the advent and widespread use of solid-state drives, beginning with hard disk drives.
Artificial intelligence (AI), machine learning, and deep learning are becoming a significant part of how businesses operate and use technology. Deep learning—only one small part of machine learning that’s concerned with algorithms based on the human brain—is expected to reach a value of $935 billion in the U.S. software market by 2025.
Suspend disbelief for a moment and ponder the following questions: What would your business look like if we made it economical to run your storage infrastructure at speeds closer to that of memory than that of disk storage? How fast would your applications run? What business models would it open up? How much competitive advantage can you gain?
Modern hosting and service providers often face the challenge of managing the cost efficiencies of their platform. A common solution is to deploy a multi-tenant or multi-instance architecture in which many customers share the same hardware. The reuse of hardware over many clients drives down costs and also reduces the required ongoing administration.
Multi-tenant deployments host many clients in the same instance of software while segregating the client data through configuration. Multi-instance designs are similar but run one instance of software per client. To the storage tier, both approaches require many sub-ecosystems to run simultaneously in a shared space and will cause similar access challenges:
- Unpredictability of usage
- Height of individual usage spikes
- Scale versus storage performance (more clients translates into a more random and parallel workload)
SSD’s are like cordless phones and DVD’s. They made an improvement on an existing technology but didn’t revolutionize its use. In technology there is a difference between the concept of modernizing and revolutionizing. Modernizing is finding a way to do the same thing, just a little bit faster or little bit easier. Revolutionizing is either eliminating or vastly changing how something is done.
Flash is about latency and IOPs so why would it be good for Data Warehousing or Business Intelligence?
Excellent question. Yes, the typical marketing and wow-factor stats around flash are based on latencies and IOPs (Input Output Per Second). Data warehousing (DW) and Business Intelligence (BI) is normally a throughput game, so what gives?
Transactional workloads are commonly defined as being small atomic pieces of work. This is in contrast to decision support, Data Warehouse, Business Intelligence or otherwise labeled reporting systems that require fewer, larger, more sequential workloads. Updates, inserts, deletes and even small result-set selects are all included in OLTP, transactional efforts.
Violin's own Ashminder Ubhi, an Oracle expert, recently tested the OLTP (online transaction processing) storage performance of Violin Systems arrays vs. Exadata and SSD-based solutions using the popular SLOB benchmarking tool. Check out Ubhi's blog post on OLTP performance for the full story.
Ubhi's benchmarks highlight how a purpose-built flash memory array can offer benefits over products which are not designed to get the performance benefits of NAND flash technology – especially for an OLTP workload.
Back to school day.
Over at Stanford they have a speaker series that has been going on for the last few... decades, called the Stanford University Department of Electrical Engineering Computer Systems Colloquium, known to many simply as EE380. The list of past speakers is as they say, long and distinguished, and includes such industry lightweights as Joy, Lamport, Colwell, Bechtolsheim, Gray, Metcalfe, Gelsinger, Hennessy, Patterson, Brin & Page, Diffie, Mashy, Wolfram, Cerf and Kay. For a mere mortal being invited to give an EE380 talk can be an intimidating experience, which they try to make easier by telling you that there will probably be no more than 50 people in the room, thankfully they didn't mention that 10,000 people will watch the web cast online until after my talk was over. Yes, the other day Bennett and Rowett were added to the list of "past EE380 speakers."
Topics: dedup, Flash Array, groomer, MLC, solid state drive, Computer Data Storage, flash memory, flash storage, garbage collection, grooming, IOPS, jon bennett, memory array, memory arrays, PCIe, server, SLC, SSD, Systems Design, Storage Array