In this episode, we talk with Rob Peglar (@PeglarR), Senior VP and CTO of Symbolic IO, a computationally defined storage vendor. Rob has been around almost as long as the GreyBeards (~40 years) and most recently was with Micron and prior to that, EMC Isilon. Rob is also on the board of SNIA.
Symbolic IO has emerged out of stealth earlier this year and intends to be shipping products by late this year/early next. Rob joined Symbolic IO in July of 2016.
What’s computational storage?
It’s all about symbolic representation of bits. Symbolic IO has come up with a way to encode bit streams into unique symbols that offer significant savings in memory space, beyond standard data compression techniques.
All that would be just fine if it was at the end of a storage interface and we would probably just call it a new form of data reduction. But Symbolic IO also incorporates persistent memory (NV-DIMMs, in the future 3D XPoint, RERam, others) and provides this symbolic data inside a server, directly through its processor data cache, in (decoded) raw data form.
Symbolic IO provides a translation layer between persistent memory and processor cache that decodes the symbolic representation of the data in persistent memory for data reads on the way into data cache and encodes the symbolic representation of the raw data for data writes on the way out of cache to persistent memory.
Rob says that the mathematics are there to show that Symbolic IO’s data reduction is significant and that the decode/encode functionality can be done in a matter of a few clock cycles per cache (line) access on modern (Intel) processors.
The system continually monitors the data it sees to determine what the optimum encoding should be and can change its symbolic table to provide more memory savings for new data written to persistent memory.
All this reminds the GreyBeards of Huffman encoding algorithms for data compression (which one of us helped deploy on a previous [unnamed] storage product). Huffman encoding transformed ASCII (8-bit) characters into variable length bit streams.
Symbolic IO will offer 3 products:,
- IRIS™ Compute, which provides a persistent memory storage, accessed using something like the Linux pmem library and includes Symbolic StoreModules™ (persistent memory hardware);
- IRIS Vault, which is an appliance with its own (IRIS) infused Linux (Symbolic’s SymCE™) OS plus Symbolic IO StoreModules, that can run any Linux application without change accessing the persistent memory and offers full data security, next generation snapshot-/clone-like capabilities with BLINK™ full storage backups, and offers enhanced physical security with the removable, IRIS Advanced EYE ASIC; and
- IRIS Store, which extends the IRIS Vault and IRIS Compute above with more tiers of storage, using Symbolic IO StoreModules as Tier1, PCIe (flash) storage as Tier 2 and external SSD storage as Tier 3 storage.
For more information on Symbolic IO’s three products, so we would encourage you to read their website (linked above).
The podcast runs long, over 47 minutes, and was wide ranging, discussing some of the history of processor/memory/information technologies. It was very easy to talk with Rob and both Howard and I have known Rob for years, across multiple vendors & organizations. Listen to the podcast to learn more.
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Rob Peglar, Senior VP and CTO, Symbolic IO
Rob Peglar is the Senior Vice President and Chief Technology Officer of Symbolic IO. Rob is a seasoned technology executive with 39 years of data storage, network and compute-related experience, is a published author and is active on many industry boards, providing insight and guidance. He brings a vast knowledge of strategy and industry trends to Symbolic IO. Rob is also on the Board of Directors for the Storage Networking Industry Association (SNIA) and an advisor for the Flash Memory Summit. His role at Symbolic IO will include working with the management team to help drive the future product portfolio, executive-level forecasting and customer/partner interaction from early-stage negotiations through implementation and deployment.
Prior to joining Symbolic IO, Rob was the Vice President, Advanced Storage at Micron Technology, where he led next-generation technology and architecture enablement efforts of Micron’s Storage Business Unit, driving storage solution development with strategic customers and partners. Previously he was the CTO, Americas for EMC where he led the entire CTO functions for the Americas. He has also held senior level positions at Xiotech Corporation, StorageTek and ETA Systems.
Rob’s extensive experience in data management, analytics, high-performance computing, non-volatile memory, distributed cluster architectures, filesystems, I/O performance optimization, cloud storage and replication and archiving, networking, virtualization makes him a sought after industry expert and board member. He was named an EMC Elect in 2014, 2015 and 2016. He was one of 25 senior executives worldwide selected for the CRN ‘Storage Superstars’ Award in 2010.
The Number for the Library of Congress [LC] are, as usual, way off the mark. The amount of available storage at the LC is available at the following web location, http://www.digitalpreservation.gov/meetings/DSA2016/Day1/CarlWattsLCStorageEnvironment.pdf.
The idea that you can get a 10:1 compression ratio on storage data is an over rose’ idea and will very by the type of content being stored. If you are talking about content (digital object that represent item), which may have already been compressed via it’s file type [like .jp2, .jpg, .pdf, .gz, etc..] there is nothing that this storage system can but just store it at a 1:1 of in some maybe a some a slight increase or a slight increase to the file storage space.
If you are talking purely about structure data, VM’s and application, then I could see the appeal.
Carl,
Thanks for your comments. We couldn’t agree more that different data will have different reduction (compression) rates. How well Symbolic IO will work is subject to speculation until we see more. That being said there are always better ways coming out to reduce data.
But it’s not just the data reduction potential that matters, it’s how fast you can accomplish it. Symbolic IO seems to have taken all this to a whole other level. I look forward to seeing their product deployed against real field/customer data and analyzing its results for both IO performance and data reduction levels.
GBs
Carl,
BTW, nice discussion on LoC storage in the link you provided.
GBs