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How Do SSDs Work? – And why I upgraded my MacBook Pro to one.

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How do SSDs work in the first place, and how do they compare with new technologies, like Intel Optane?

To understand how and why SSDs are different from spinning discs, we need to talk a little bit about hard drives. A hard drive stores data on a series of spinning magnetic disks, called platters. There’s an actuator arm with read/write heads attached to it. This arm positions the read-write heads over the correct area of the drive to read or write information.

Because the drive heads must align over an area of the disk in order to read or write data (and the disk is constantly spinning), there’s a non-zero wait time before data can be accessed. The drive may need to read from multiple locations in order to launch a program or load a file, which means it may have to wait for the platters to spin into the proper position multiple times before it can complete the command. If a drive is asleep or in a low-power state, it can take several seconds more for the disk to spin up to full power and begin operating.

From the very beginning, it was clear hard drives couldn’t possibly match the speeds at which CPUs could operate. Latency in HDDs is measured in milliseconds, compared with nanoseconds for your typical CPU. One millisecond is 1,000,000 nanoseconds, and it typically takes a hard drive 10-15 milliseconds to find data on the drive and begin reading it. The hard drive industry introduced smaller platters, on-disk memory caches, and faster spindle speeds to counteract this trend, but there’s only so fast drives can spin. Western Digital’s 10,000 RPM VelociRaptor family is the fastest set of drives ever built for the consumer market, while some enterprise drives spun up to 15,000 RPM. The problem is, even the fastest spinning drive with the largest caches and smallest platters are still achingly slow as far as your CPU is concerned.

How SSDs Are Different

“If I had asked people what they wanted, they would have said faster horses.” — Henry Ford

Solid-state drives are called that specifically because they don’t rely on moving parts or spinning disks. Instead, data is saved to a pool of NAND flash. NAND itself is made up of what are called floating gate transistors. Unlike the transistor designs used in DRAM, which must be refreshed multiple times per second, NAND flash is designed to retain its charge state even when not powered up. This makes NAND a type of non-volatile memory.

Flash cell structure

The diagram above shows a simple flash cell design. Electrons are stored in the floating gate, which then reads as charged “0” or not-charged “1.” Yes, in NAND flash, a 0 means data is stored in a cell — it’s the opposite of how we typically think of a zero or one. NAND flash is organized in a grid. The entire grid layout is referred to as a block, while the individual rows that make up the grid are called a page. Common page sizes are 2K, 4K, 8K, or 16K, with 128 to 256 pages per block. Block size therefore typically varies between 256KB and 4MB.

One advantage of this system should be immediately obvious. Because SSDs have no moving parts, they can operate at speeds far above those of a typical HDD. The following chart shows the access latency for typical storage mediums given in microseconds.

SSD-Latency

Image by CodeCapsule

NAND is nowhere near as fast as main memory, but it’s multiple orders of magnitude faster than a hard drive. While write latencies are significantly slower for NAND flash than read latencies, they still outstrip traditional spinning media.

There are two things to notice in the above chart. First, note how adding more bits per cell of NAND has a significant impact on the memory’s performance. It’s worse for writes as opposed to reads — typical triple-level-cell (TLC) latency is 4x worse compared with single-level cell (SLC) NAND for reads, but 6x worse for writes. Erase latencies are also significantly impacted. The impact isn’t proportional, either — TLC NAND is nearly twice as slow as MLC NAND, despite holding just 50% more data (three bits per cell, instead of two).

TLC NAND

TLC NAND voltages

The reason TLC NAND is slower than MLC or SLC has to do with how data moves in and out of the NAND cell. With SLC NAND, the controller only needs to know if the bit is a 0 or a 1. With MLC NAND, the cell may have four values — 00, 01, 10, or 11. With TLC NAND, the cell can have eight values. Reading the proper value out of the cell requires the memory controller use a very precise voltage to ascertain whether any particular cell is charged or not.

Reads, Writes, and Erasure

One of the functional limitations of SSDs is while they can read and write data very quickly to an empty drive, overwriting data is much slower. This is because while SSDs read data at the page level (meaning from individual rows within the NAND memory grid) and can write at the page level, assuming surrounding cells are empty, they can only erase data at the block level. This is because the act of erasing NAND flash requires a high amount of voltage. While you can theoretically erase NAND at the page level, the amount of voltage required stresses the individual cells around the cells that are being re-written. Erasing data at the block level helps mitigate this problem.

The only way for an SSD to update an existing page is to copy the contents of the entire block into memory, erase the block, and then write the contents of the old block the updated page. If the drive is full and there are no empty pages available, the SSD must first scan for blocks that are marked for deletion but that haven’t been deleted yet, erase them, and then write the data to the now-erased page. This is why SSDs can become slower as they age — a mostly-empty drive is full of blocks that can be written immediately, a mostly-full drive is more likely to be forced through the entire program/erase sequence.

If you’ve used SSDs, you’ve likely heard of something called “garbage collection.” Garbage collection is a background process that allows a drive to mitigate the performance impact of the program/erase cycle by performing certain tasks in the background. The following image steps through the garbage collection process.

Garbage collection

Image courtesy of Wikipedia

Note in this example, the drive has taken advantage of the fact that it can write very quickly to empty pages by writing new values for the first four blocks (A’-D’). It’s also written two new blocks, E and H. Blocks A-D are now marked as stale, meaning they contain information the drive has marked as out-of-date. During an idle period, the SSD will move the fresh pages over to a new block, erase the old block, and mark it as free space. This means the next time the SSD needs to perform a write, it can write directly to the now-empty Block X, rather than performing the program/erase cycle.

The next concept I want to discuss is TRIM. When you delete a file from Windows on a typical hard drive, the file isn’t deleted immediately. Instead, the operating system tells the hard drive it can overwrite the physical area of the disk where that data was stored the next time it needs to perform a write. This is why it’s possible to undelete files (and why deleting files in Windows doesn’t typically clear much physical disk space until you empty the recycling bin). With a traditional HDD, the OS doesn’t need to pay attention to where data is being written or what the relative state of the blocks or pages is. With an SSD, this matters.

The TRIM command allows the operating system to tell the SSD it can skip rewriting certain data the next time it performs a block erase. This lowers the total amount of data the drive writes and increases SSD longevity. Both reads and writes damage NAND flash, but writes do far more damage than reads. Fortunately, block-level longevity has not proven to be an issue in modern NAND flash. More data on SSD longevity, courtesy of the Tech Report, can be found here.

The last two concepts we want to talk about are wear leveling and write amplification. Because SSDs write data to pages but erase data in blocks, the amount of data being written to the drive is always larger than the actual update. If you make a change to a 4KB file, for example, the entire block that 4K file sits within must be updated and rewritten. Depending on the number of pages per block and the size of the pages, you might end up writing 4MB worth of data to update a 4KB file. Garbage collection reduces the impact of write amplification, as does the TRIM command. Keeping a significant chunk of the drive free and/or manufacturer over-provisioning can also reduce the impact of write amplification.

Wear leveling refers to the practice of ensuring certain NAND blocks aren’t written and erased more often than others. While wear leveling increases a drive’s life expectancy and endurance by writing to the NAND equally, it can actually increase write amplification. In other to distribute writes evenly across the disk, it’s sometimes necessary to program and erase blocks even though their contents haven’t actually changed. A good wear leveling algorithm seeks to balance these impacts.

The SSD Controller

It should be obvious by now SSDs require much more sophisticated control mechanisms than hard drives do. That’s not to diss magnetic media — I actually think HDDs deserve more respect than they are given. The mechanical challenges involved in balancing multiple read-write heads nanometers above platters that spin at 5,400 to 10,000 RPM are nothing to sneeze at. The fact that HDDs perform this challenge while pioneering new methods of recording to magnetic media and eventually wind up selling drives at 3-5 cents per gigabyte is simply incredible.

SSD controller

A typical SSD controller

SSD controllers, however, are in a class by themselves. They often have a DDR3 memory pool to help with managing the NAND itself. Many drives also incorporate single-level cell caches that act as buffers, increasing drive performance by dedicating fast NAND to read/write cycles. Because the NAND flash in an SSD is typically connected to the controller through a series of parallel memory channels, you can think of the drive controller as performing some of the same load balancing work as a high-end storage array — SSDs don’t deploy RAID internally, but wear leveling, garbage collection, and SLC cache management all have parallels in the big iron world.

Some drives also use data compression algorithms to reduce total number of writes and improve the drive’s lifespan. The SSD controller handles error correction, and the algorithms that control for single-bit errors have become increasingly complex as time has passed.

Unfortunately, we can’t go into too much detail on SSD controllers because companies lock down their various secret sauces. Much of NAND flash’s performance is determined by the underlying controller, and companies aren’t willing to lift the lid too far on how they do what they do, lest they hand a competitor an advantage.

The Road Ahead

NAND flash offers an enormous improvement over hard drives, but it isn’t without its own drawbacks and challenges. Drive capacities and price-per-gigabyte are expected to continue to rise and fall respectively, but there’s little chance SSDs will catch hard drives in price-per-gigabyte. Shrinking process nodes are a significant challenge for NAND flash — while most hardware improves as the node shrinks, NAND becomes more fragile. Data retention times and write performance are intrinsically lower for 20nm NAND than 40nm NAND, even if data density and total capacity are vastly improved.

Thus far, SSD manufacturers have delivered better performance by offering faster data standards, more bandwidth, and more channels per controller — plus the use of SLC caches we mentioned earlier. Nonetheless, in the long run, it’s assumed NAND will be replaced by something else.

What that something else will look like is still open for debate. Both magnetic RAM and phase change memory have presented themselves as candidates, though both technologies are still in early stages and must overcome significant challenges to actually compete as a replacement to NAND. Whether consumers would notice the difference is an open question. If you’ve upgraded from NAND to an SSD and then upgraded to a faster SSD, you’re likely aware the gap between HDDs and SSDs is much larger than the SSD-to-SSD gap, even when upgrading from a relatively modest drive. Improving access times from milliseconds to microseconds matters a great deal, but improving them from microseconds to nanoseconds might fall below what humans can realistically perceive in most cases.

Intel’s 3D XPoint (marketed as Intel Optane) has emerged as one potential challenger to NAND flash, and the only current alternative technology in mainstream production. Optane SSDs offer similar sequential performance to current NAND flash drives, but with vastly better performance at low drive queues. Drive latency is also roughly half of NAND flash (10 microseconds, versus 20) and vastly higher endurance (30 full drive-writes per day, compared with 10 full drive writes per day for a high-end Intel SSD).

Optane1

Intel Optane performance targets

The first Optane SSDs have debuted as excellent add-ons for Kaby Lake and Coffee Lake. Still, Optane is still too expensive to match NAND flash, which benefits from substantial economies of scale, but this could change in the future. NAND will stay king of the hill for at least the next 3-4 years. But past that point we could see Optane starting to replace it in volume, depending on how Intel and Micron scale the technology and how well 3D NAND flash continues to expand its cell layers (64-layer NAND is shipping from multiple players), with roadmaps for 96 and even 128 layers on the horizon.

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Inside JD.com, the giant Chinese firm that could eat Amazon alive

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Pujiang Pu is a smiley, medium-built man in his mid-forties with stylish glasses, a bling gold watch, and a red JD lanyard around his neck. Along with many of the 150,000 employees of JD.com – a city-size e-commerce store sometimes referred to as the Amazon of China – he lives in a free dorm near one of the company’s 500 gigantic warehouses. The warehouse I visit is in Jiading, 30km north-west of Shanghai’s city centre. Hundreds of people work here, and at 100,000 square metres in size it sits on a JD complex so big it would take at least 45 minutes to walk from one end to the other.

I am allowed here as part of a rare, highly supervised press visit, and warehouse manager Pu is our tour guide. I am not shown everything, but enough to impress – or, as some analysts believe, to show that JD is a kind of company Amazon ultimately wants to become.

JD wasn’t always that big. It started out as a small brick and mortar store in Beijing, founded in 1998 by Richard Liu. Then in 2004, Liu moved it online and JD.com, short for Jingdong, was born. Fast-forward to today, and the firm is worth more than $55 billion. In February, logistics magazine DC Velocity called it “the biggest company you may not know all that much about”. Not for much longer though – JD is so growing so fast at home in China and expanding so rapidly into other markets such as Thailand, Indonesia and Vietnam and most recently Europe, that even the most devout Amazonians will soon sit up and notice.

The main reason Pu stays in a dorm on site, and away from his family, is to ensure he can meet key performance indicators set by the firm. Sometimes, especially during JD.com’s annual shopping event, he has to work late into the night.

But the future of these dorms is uncertain. Many traditional warehouse jobs like stacking shelves and packing boxes at JD are likely to go to robots in the coming years, as the company starts to automate everything that can sensibly be automated. The tech giant is now busy retraining some staff to take on new roles that machines can’t yet do. Pu’s warehouses have some of the firm’s most advanced robotics – and he gets really excited talking about the autonomous forklift trucks and delivery drones.

These drones have been in the news a lot lately. Remember when Amazon’s boss Jeff Bezos made claims that his firm would soon drop parcels off at your doorstep? Well, that was in 2013 – and, some small-scale trials aside, it’s still not happening. But it’s very much happening at JD – since March 2016, its drones have been delivering products across China, having clocked over 300,000 minutes of flight time. “Today we have over 200 people working on our drone programme,” says Zheng Cui, director of the firm’s drone R&D centre in Xi’an.

The drones come in various shapes and sizes, but the quickest ones can fly up to 100km/h and have a range of 100km. So far though, the furthest delivery has been 15km and that drone flew much slower than 100km/h – but you have to start somewhere. What the drones can’t do yet, JD does with its 65,000 van drivers and couriers.

The drone efforts haven’t gone unnoticed though, and other companies are keen to replicate JD’s air delivery success. Cui says more and more firms are getting in touch to buy their drones. “We’ve just got an order for 1,000 at the beginning of this year,” he adds.

Those drones are still fairly small, but JD is busy developing larger ones that can carry up to five tonnes. “They’ll transfer inventory from one warehouse to another,” says Cui. “Within three years we’re looking at having a couple of thousand,” he says – and they will take off right from existing small airports near the company’s warehouses.

It’s not just the drones that make the Chinese behemoth different from Western e-commerce stores, though. Robots at JD are everywhere. In the warehouse I visit, machines stack tens of thousands of products on 24-metre-high shelves. Over the road from where I am, another fully automated warehouse can pack and ship 200,000 products a day. Robots are not alone yet, though: the fully automated warehouse has four human helpers.

Automation, growth, scale – the mega but still relatively unknown giant seems unlikely to slow down. Its revenues are growing 40 per cent a year, up to $55.7 billion in 2017. The company’s spokespeople tell us proudly the firm is the third largest “internet company” in the world by revenue after Google and Amazon, but ahead of companies like Facebook, eBay and Alibaba, its biggest rival.

It has major backers such as Tencent — the largest internet company in China by market cap and the owner of WeChat. Other investors are Walmart, which has a ten per cent stake, and even Google, which last month announced it was investing $550 million into JD to help it expand further outside China.

And the e-commerce giant is busy doing just that. In January, it opened its first European office, in Paris. It now aims to open another one in Milan, and is actively partnering with Spanish and other European brands – especially luxury ones. In 2017, Chinese made up 32 per cent of the worldwide luxury market.

JD’s response: last October, it launched Toplife, a platform for luxury buyers that can benefit from same-day deliveries and premium services, such as ultra-clean and secure warehouses with special air filters. Over just a few months, Toplife has already signed up 20 brands, including Saint Laurent and Alexander McQueen. Amazon beware.

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LG G7 ThinQ Is Now Available In the US for $750

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LG waited longer than normal to announce its big 2018 flagship phone, but it finally took the wraps off the LG G7 ThinQ a few weeks ago. Today, the phone is available for purchase on most US carriers. While LG has had trouble competing with the likes of Samsung, it’s still targeting the same premium space. Although, it’s got an iPhone-style screen notch now. That’s what consumers want, right?

The LG G7 ThinQ is the epitome of all things 2018 in smartphone design. It has a glass back, dual cameras, and a display notch that isn’t done particularly well. The missing bit of screen provides a place for the camera, earpiece, and some other sensors. It does seem a little excessively large for how compact these components are, though. In addition, the G7 has a “chin” at the bottom with a larger bezel than the top and bottom. This asymmetric look isn’t as striking as the iPhone X it imitates. The 6.1-inch 1440p display is also an OLED, which lacks the vibrancy of modern OLED panels.

Inside, this phone has all the current flagship hardware you’d expect with a Snapdragon 845, 64GB of storage, and 4GB of RAM. Unlike many other current smartphones, the company has opted to keep the headphone jack for the G7 ThinQ. LG also touts the G7’s unique speaker design that uses the entire chassis as a resonator to boost sound output.

You may be wondering about the name — specifically the “ThinQ” bit. Well, that’s LG’s expanded brand for all its AI technologies. What that means for the G7 is that there’s an AI mode in the camera that looks for objects it can identify and offers possible filters. It’s not very accurate or useful, but LG didn’t even develop any AI software or hardware for this phone. It just licensed a machine vision library from a third-party.

The LG G7 ThinQ is available from all major carriers in the US except AT&T. Apparently, AT&T chose to sell the LG V35 instead of the G7. This marks the third variant of the V30 that LG has sold since it debuted last year. At other carriers, the G7 ThinQ will run you $750, give or take a few dollars. Carriers offer payment plans to split the cost over two years. It will launch on Google’s Project Fi soon, as well. If you don’t want to go through carriers, the phone is also available from Amazon.

 

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