What does the relatively new acronym MCI have to do with the accelerated adoption of in-memory computing? I’d say everything.
MCI stands for Memory Channel Interface storage (a.k.a MCS - Memory Channel Storage) and it essentially allows you to put NAND flash storage into a DIMM form factor and enable it to interface with a CPU via a standard memory controller. Put another way, MCI provides a drop-in replacement for DDR3 RDIMMs with 10x the memory capacity and a 10x reduction in price.
Historically, one of the major inhibitors behind in-memory computing adoption was the high cost of DRAM relative to disks and flash storage. While advantages such as 100x performance, lower power consumption and higher reliability were clearly known for years, the price delta was and is still relatively high:
While spinning HDDs are essentially cost-free for enterprise consumption, and flash storage is enjoying mass adoption, DRAM storage still lags behind simply due to higher cost.
If prices are relatively similar between MCI and PCI-E storage, what makes MCI so much more important? The answer is direct memory access vs. block-based device.
All of the PCI-E flash storage today (FusionIO, Violin, basic SSDs, etc.) are recognized by the OS as block devices, i.e. essentially fast hard drives. Applications access these devices via typical file interface involving all typical marshaling, buffering, OS context switching, networking and IO overhead.
MCI provides an option to view its flash storage simply as main system memory, eliminating all the OS/IO/network overhead, while working directly via a highly optimized memory controller - the same controller that handles massive CPU-DDR3 data exchange - and enabling software like GridGain’s to access the flash storage as normal memory. This is a game changer and potentially a final frontier in the storage placement technology. In fact, you can’t place application data any closer to the CPU than the main memory and that is precisely what MCI enables us to do on terabyte and petabyte scale.
Moreover, MCI provides direct improvements over PCI-E storage. Diablo Technology, the pioneer behind MCI technology, claims that MCI is more performant (lower latencies and higher bandwidth) than typical PCI-E and SATA SSDs while providing ever elusive constant latency that is unachievable with standard PCE-E or SSD technologies.
Another important characteristic of MCI storage is the plug-n-play fashion in which it can be used - no custom hardware, no custom software required. Imagine, for example, an array of 100 micro-servers (ARM-based servers in micro form factor), each with 256GB of MCI-based system memory, drawing less than 10 watts of power, costing less than $1000 each.
You now have a cluster with 25TB in-memory storage, 200 cores of processing power, running standard Linux, drawing around 1000 watts for about the same cost as a fully loaded Tesla Model S. Put GridGain’s In-Memory Computing Stack on it and you have an eco-friendly, cost effective, powerful real-time big data cluster ready for any task.
MCI stands for Memory Channel Interface storage (a.k.a MCS - Memory Channel Storage) and it essentially allows you to put NAND flash storage into a DIMM form factor and enable it to interface with a CPU via a standard memory controller. Put another way, MCI provides a drop-in replacement for DDR3 RDIMMs with 10x the memory capacity and a 10x reduction in price.
Historically, one of the major inhibitors behind in-memory computing adoption was the high cost of DRAM relative to disks and flash storage. While advantages such as 100x performance, lower power consumption and higher reliability were clearly known for years, the price delta was and is still relatively high:
| Storage | ~ Performance | ~ Price |
|---|---|---|
| 1TB DDR3 RDIMM (32 DIMMs) | 1000-10,000x | $20,000 |
| 1TB PCI-E | 10-100x | $4,000 |
| 1TB SSD | 10-100x | $1,000 |
| 1TB HDD | 1x | $100 |
While spinning HDDs are essentially cost-free for enterprise consumption, and flash storage is enjoying mass adoption, DRAM storage still lags behind simply due to higher cost.
MCI-based storage is about to change this once and for all as it aims to bring the price of flash-based DRAM to the same level as today’s SSD and PCI-E flash storage.
MCI vs. PCI-E Flash
If prices are relatively similar between MCI and PCI-E storage, what makes MCI so much more important? The answer is direct memory access vs. block-based device.
All of the PCI-E flash storage today (FusionIO, Violin, basic SSDs, etc.) are recognized by the OS as block devices, i.e. essentially fast hard drives. Applications access these devices via typical file interface involving all typical marshaling, buffering, OS context switching, networking and IO overhead.
MCI provides an option to view its flash storage simply as main system memory, eliminating all the OS/IO/network overhead, while working directly via a highly optimized memory controller - the same controller that handles massive CPU-DDR3 data exchange - and enabling software like GridGain’s to access the flash storage as normal memory. This is a game changer and potentially a final frontier in the storage placement technology. In fact, you can’t place application data any closer to the CPU than the main memory and that is precisely what MCI enables us to do on terabyte and petabyte scale.
Moreover, MCI provides direct improvements over PCI-E storage. Diablo Technology, the pioneer behind MCI technology, claims that MCI is more performant (lower latencies and higher bandwidth) than typical PCI-E and SATA SSDs while providing ever elusive constant latency that is unachievable with standard PCE-E or SSD technologies.
Plug-n-Play
Another important characteristic of MCI storage is the plug-n-play fashion in which it can be used - no custom hardware, no custom software required. Imagine, for example, an array of 100 micro-servers (ARM-based servers in micro form factor), each with 256GB of MCI-based system memory, drawing less than 10 watts of power, costing less than $1000 each.
You now have a cluster with 25TB in-memory storage, 200 cores of processing power, running standard Linux, drawing around 1000 watts for about the same cost as a fully loaded Tesla Model S. Put GridGain’s In-Memory Computing Stack on it and you have an eco-friendly, cost effective, powerful real-time big data cluster ready for any task.