question: How does Intel Optane store data that is frequently used to speed loading times up?
comment: the optane memory is used for caching. so things that you frequently use will be stored into this cache and be faster since it's optane. what makes optane faster is it's specific type of memory that is much faster than hdd/ssd's and reaching ram speeds.
passages: Designed to process data that is substantially larger than memory at in-memory speeds, BLU Acceleration prefetches and streams data into the processing engine—advancing beyond system memory to in-CPU memory optimization. It uses a specialized in-memory optimized columnar prefetching algorithm to determine a few milliseconds in advance what data should be loaded into RAM; every algorithm has been designed to minimize access to RAM, and maximize processing time in L3 and L2 caches, which are an order of magnitude faster than RAM.,
   BLU Acceleration is the second generation of the technology that originated in the Blink project, which was started at the IBM Almaden Research Center in 2006. Aimed primarily at "read-mostly" business intelligence (BI) query processing, Blink combined the scale-out of multi-core processors with dynamic random-access memory (DRAM) to store a copy of a data mart completely in memory. It also used proprietary compression techniques and algorithms that allowed most SQL queries to be performed directly against compressed data (as opposed to requiring data to be decompressed before processing could take place).
   BULLET::::- Nitrox and Octeon processors from Cavium, Inc. contain high-speed hardware deflate and inflate engines compatible with both ZLIB and GZIP with some devices able to handle multiple simultaneous data streams.
  
  BULLET::::- HDL-Deflate GPL FPGA implementation.
  
  BULLET::::- Intel Communications Chipset 89xx Series (Cave Creek) for the Intel Xeon E5-2600 and E5-2400 Processor Series (Sandy Bridge-EP/EN) supports hardware compression and decompression using QuickAssist Technology. Depending on the chipset, compression and decompression rates of 5Gbit/s, 10Gbit/s, or 20Gbit/s are available.
  
  Section::::Decoder/decompressor.
   Once encoded, data is packed as tightly as possible in a collection of bits that equal the register width of the CPU of the server being used. This results in fewer I/Os (because the data is smaller), better memory utilization (because more data can be stored in memory), and fewer CPU cycles (because the data is "register aligned").
  
  Section::::Technical information.:Data skipping.
   In 2008, Intel began shipping mainstream solid-state drives (SSDs) with up to 160 GB storage capacities. As with their CPUs, Intel develops SSD chips using ever-smaller nanometer processes. These SSDs make use of industry standards such as NAND flash, mSATA, PCIe, and NVMe. In 2017, Intel introduced SSDs based on 3D XPoint technology under the Optane brand name.
  
  Section::::Product and market history.:Supercomputers.
   Conceptually, BLU Acceleration‘s data skipping is similar to the Zone Map technology found in the PureData System for Analytics family. However, unlike Zone Maps, the metadata stored in the synopsis table isn‘t tied to any particular page or extent boundary―instead, it‘s tied to a specific "chunk" of data records. Data skipping can deliver an order of magnitude in savings across compute resources (CPU, RAM, and I/O).
  
  Section::::Technical information.:CPU acceleration.
   Dell EMC Unity’s Multicore Cache dynamically adjusts cache sizes according to the read and write operation, minimizing forced flushing when the high watermark level on the cache is reached. This functionality can be augmented through the implementation of Dell EMC’s fully automated storage tiering (FAST) cache. FAST cache monitors incoming I/O for access frequency and automatically copies frequently accessed data from the back-end drives into the cache. It can extend existing cache capacities up to 2 terabytes.
   BULLET::::- Recently Used Documents - The MRU menu maintains not just a large collection of previously used documents, but also checks each file for availability. Files which are no longer present on the system are shown greyed out. In addition, the history of the MRU is categorized into distinct period such as "Just Now", "Today", "Thursday" and "Last Week".
  
  Section::::Node based editor.
   In addition, BLU Acceleration is engineered so that the majority of memory access occurs in a CPU cache and not by accessing data from RAM over and over again. By operating almost exclusively on data in a CPU cache and not in RAM, BLU Acceleration minimizes latency and is able to keep CPUs busy.
   BLU Acceleration does not require indexes, aggregates or tuning. BLU Acceleration is integrated in Version 10.5 of IBM DB2 for Linux, Unix and Windows,(DB2 for LUW) and uses the same storage and memory constructs (i.e., storage groups, table spaces, and buffer pools), SQL language interfaces, and administration tools as traditional DB2 for LUW databases. BLU Acceleration is available on both IBM POWER and x86 processor architectures.
  
  Section::::History.
   BULLET::::- Does not need to check disk integrity at start-up, meaning a shorter boot time.
  
  BULLET::::- Dynamic file system configuration for performance optimization.
  
  BULLET::::- Full data-exchangeability with Microsoft Windows, via the Reliance Windows Driver.
  
  Reliance has a maximum volume size of 2 TB and a maximum file size of 4 GB.
  
  Section::::Products.:Reliance family.:Reliance Nitro.
  
  Released in 2009, Reliance Nitro is a file system developed from Reliance; it improved on the performance of original Reliance, primarily by adding a tree-based directory architecture facilitating faster look-ups. The maximum volume size on Reliance Nitro is 32 TB; maximum file size is constrained only by free space.
   With BLU Acceleration, values are compressed such that their order is preserved, which means they can be compared to each other while they are compressed.This allows the most common comparisons in SQL predicates to be performed on encoded values without needing to decompress the data, thereby accelerating evaluations, reducing memory requirements and lowering processing needs for queries at runtime.,
   Storage caches (including disk caches for files, or processor caches for either code or data) work also like a lookup table. The table is built with very fast memory instead of being stored on slower external memory, and maintains two pieces of data for a sub-range of bits composing an external memory (or disk) address (notably the lowest bits of any possible external address):
   Napatech´s product portfolio of network accelerators span speeds ranging from 1Gbit/s up to 100Gbit/s of speed with 1, 2 or 4-port variants. Its first product was an accelerator launched in December 2003 which supported 10Gbit/s network speeds. Up until the first quarter of 2014, the company has produced approximately 40+ different models of accelerators. Some of the most important features being the capture of all network data at full line rate, and guaranteed delivery of data with zero packet loss.
   BULLET::::3. Data is promoted to the SSD based on its access frequency. The frequency is detected at the block level and below file system memory cache. Data migration happens in 128 KB chunks during idle or light I/O periods.
  
  BULLET::::4. Operating system and other critical documents are always cached on the SSD. Applications are likely to be handled similarly. A regular file can reside on both devices.
  
  Section::::See also.
  
  BULLET::::- bcache, dm-cache, and Flashcache on Linux
  
  BULLET::::- Smart Response Technology — a similar technology from Intel (for desktops)
  
  BULLET::::- Intel Turbo Memory
   In March 2009, the company introduced a new version of reQall that includes a patent-pending “Memory Jogger” that analyzes various aspects of the user’s current situation (time, location and upcoming calendar events) to provide a dynamically updated display of relevant to-dos and notes. The Memory Jogger proactively provides contextually-relevant reminders rather than relying on the user to seek information by accessing a static to-do list or calendar.
   While the receiver holds up to 30 days of data, the Dexcom Data Manager 3 (DM3) software allows data downloads from the Dexcom CGM systems to a computer. This provides users the ability to track their trends and progress over time. DM3 works with all versions of SEVEN Receivers. With the SEVEN PLUS, meal, insulin, health, and activity information entered can be reviewed later with the DM3 software. A1c values can also be entered in the software for tracking and viewing improvements.
  
  Section::::Products.:G4 Platinum.
   In early March 2017, AMD Ryzen became available, bringing native support for SATA Express to the AMD Socket AM4 platform, through use of its accompanying X370, X300, B350, A320 and A300 chipsets. Ryzen also supports M.2 and other forms of PCI Express storage devices, using up to the total of eight PCI Express 3.0 lanes provided by the chipset and the AM4 CPU. As a result, Ryzen provides bandwidths of up to 7.88 GB/s for connected PCI Express storage devices.
  
  Section::::Features.
   In 1996, IBM began experimenting with compression, and in 2000 IBM announced its Memory eXpansion Technology (MXT). MXT was a stand-alone chip which acted as a CPU cache between the CPU and memory controller. MXT had an integrated compression engine which compressed all data heading to/from physical memory. Subsequent testing of the technology by Intel showed 5–20% overall system performance improvement, similar to the results obtained by PC Magazine with Hurricane.
  
  Section::::History.:Recent developments.
  
  BULLET::::- In early 2008, a Linux project named zram (originally called compcache) was released; in a 2013 update, it was incorporated into Chrome OS and Android 4.4
   BULLET::::- LBNL’s SRMs have been used in production over the last few years to support intensive robust data movement between BNL to NERSC at a rate of about 10,000 files (about 1 TB) per week in an automated fashion. This arrangement resulted in a 50X reduction in the error rates, from 1% to 0.02% in the STAR project.
   SQLite stores the entire database (definitions, tables, indices, and the data itself) as a single cross-platform file on a host machine. It implements this simple design by locking the entire database file during writing. SQLite read operations can be multitasked, though writes can only be performed sequentially.
   Intel distinguishes between "Intel Optane Memory" and "Intel Optane SSDs". As a memory component, Optane requires specific chipset and CPU support. As an ordinary SSD, Optane is broadly compatible with a very wide range of systems, and its main requirements are much like any other SSD – ability to be plugged into the hardware, operating system, BIOS/UEFI and driver support for NVMe, and adequate cooling.
   Another technology introduced by the company in 2009 is IntelliWrite, an advanced file-system driver designed to leverage Windows’ file system “Best Fit” file-write design in order to write a file in a non-fragmented state. IntelliWrite is designed to prevent most fragmentation before it happens in Windows computer systems, allowing for better file write performance plus compatibility and interoperability with other storage management products.
  
  Section::::Company history.
   Section::::Apps.:Glucose Buddy.
  
  Azumio released Glucose Buddy in October 2011 with the aim of digitizing the paper-and-pen logging systems for diabetics. Users can manually enter glucose numbers, carbohydrate consumption, insulin dosages, and activities into Glucose Buddy. This data is then synced onto the user's account, allowing access from multiple devices including a desktop web portal. Glucose Buddy plots data into graphs which can be exported and emailed to a user's physician.
  
  Section::::Apps.:Instant Fitness.
   Since the introduction of VMAX, development has continued on both the hardware and software fronts, including the original Enginuity operating system, which was replaced by the HYPERMAX OS when the VMAX3 line was introduced in 2014 with a built-in storage hypervisor. All-Flash versions of the product line were introduced in 2016, further increasing system scalability, reliability and sub-millisecond latency. All-Flash systems accounted for 80% of all VMAX revenue as of May, 2017 according to IDC.
  
  Section::::Technology and Architecture.
  