Introduced by Solidigm
As AI adoption surges, knowledge facilities face a crucial bottleneck in storage — and conventional HDDs are on the middle of it. Knowledge that when sat idle as chilly archives is now being pulled into frequent use to construct extra correct fashions and ship higher inference outcomes. This shift from chilly knowledge to heat knowledge calls for low-latency, high-throughput storage that may deal with parallel computations. HDDs will stay the workhorse for low-cost chilly storage, however with out rethinking their position, the high-capacity storage layer dangers changing into the weakest hyperlink within the AI manufacturing unit.
"Trendy AI workloads, mixed with knowledge middle constraints, have created new challenges for HDDs," says Jeff Janukowicz, analysis vice chairman at IDC. "Whereas HDD suppliers are addressing knowledge storage development by providing bigger drives, this usually comes on the expense of slower efficiency. In consequence, the idea of 'nearline SSDs' is changing into an more and more related matter of debate throughout the trade."
Right now, AI operators want to maximise GPU utilization, handle network-attached storage effectively, and scale compute — all whereas reducing prices on more and more scarce energy and house. In an surroundings the place each watt and each sq. inch counts, says Roger Corell, senior director of AI and management advertising at Solidigm, success requires greater than a technical refresh. It requires a deeper realignment.
“It speaks to the tectonic shift within the worth of information for AI,” Corell says. “That’s the place high-capacity SSDs come into play. Together with capability, they convey efficiency and effectivity — enabling exabyte-scale storage pipelines to maintain tempo with the relentless tempo of information set dimension. All of that consumes energy and house, so we have to do it as effectively as attainable to allow extra GPU scale on this constrained surroundings.”
Excessive-capacity SSDs aren’t simply displacing HDDs — they’re eradicating one of many greatest bottlenecks on the AI manufacturing unit ground. By delivering large positive aspects in efficiency, effectivity, and density, SSDs release the ability and house wanted to push GPU scale additional. It’s much less a storage improve than a structural shift in how knowledge infrastructure is designed for the AI period.
HDDs vs. SDDs: Greater than only a {hardware} refresh
HDDs have spectacular mechanical designs, however they're made up of many shifting elements that at scale use extra power, take up more room, and fail at the next price than stable state drives. The reliance on spinning platters and mechanical learn/write heads inherently limits Enter/Output Operations Per Second (IOPS), creating bottlenecks for AI workloads that demand low latency, excessive concurrency, and sustained throughput.
HDDs additionally battle with latency-sensitive duties, because the bodily act of searching for knowledge introduces mechanical delays unsuited for real-time AI inference and coaching. Furthermore, their energy and cooling necessities improve considerably below frequent and intensive knowledge entry, decreasing effectivity as knowledge scales and warms.
In distinction, the SSD-based VAST storage answer reduces power utilization by ~$1M a 12 months, and in an AI surroundings the place each watt issues, it is a enormous benefit for SSDs. To display, Solidigm and VAST Knowledge accomplished a research analyzing the economics of information storage at exabyte scale — a quadrillion bytes, or a billion gigabytes, with an evaluation of storage energy consumption versus HDDs over a 10-year interval.
As a beginning reference level, you’d want 4 30TB HDDs to equal the capability of a single 122TB Solidigm SSD. After factoring in VAST’s knowledge discount methods made attainable by the superior efficiency of SSDs, the exabyte answer includes 3,738 Solidigm SSDs vs over 40,000 high-capacity HDDs. The research discovered that the SSD-based VAST answer consumes 77% much less storage power.
Minimizing knowledge middle footprints
"We’re delivery 122-terabyte drives to among the prime OEMs and main AI cloud service suppliers on the planet," Corell says. "While you examine an all-122TB SSD to hybrid HDD + TLC SSD configuration, they're getting a nine-to-one financial savings in knowledge middle footprint. And sure, it’s vital in these large knowledge facilities which can be constructing their very own nuclear reactors and signing hefty energy buy agreements with renewable power suppliers, but it surely’s more and more vital as you get to the regional knowledge facilities, the native knowledge facilities, and all the best way out to your edge deployments the place house can come at a premium."
That nine-to-one financial savings goes past house and energy — it lets organizations match infrastructure into beforehand unavailable areas, increase GPU scale, or construct smaller footprints.
"When you’re given X quantity of land and Y quantity of energy, you’re going to make use of it. You’re AI" Corell explains, “the place each watt and sq. inch counts, so why not use it in essentially the most environment friendly approach? Get essentially the most environment friendly storage attainable on the planet and allow better GPU scale inside that envelope that you must slot in. On an ongoing foundation, it’s going to save lots of you operational value as properly. You have got 90 % fewer storage bays to keep up, and the price related to that’s gone."
One other often-overlooked aspect, the (a lot) bigger bodily footprint of information saved on mechanical HDDs leads to a better building supplies footprint. Collectively, concrete and metal manufacturing accounts for over 15% of worldwide greenhouse fuel emissions. By decreasing the bodily footprint of storage, high-capacity SSDs may help cut back embodied concrete and steel-based emissions by greater than 80% in comparison with HDDs. And within the final section of the sustainability life cycle, which is drive end-of-life, there will likely be 90% % fewer drives to disposition. .
Reshaping chilly and archival storage methods
The transfer to SDD isn't only a storage improve; it's a elementary realignment of information infrastructure technique within the AI period, and it's choosing up velocity.
"Large hyperscalers want to wring essentially the most out of their present infrastructure, doing unnatural acts, if you’ll, with HDDs like overprovisioning them to close 90% to attempt to wring out as many IOPS per terabyte as attainable, however they’re starting to return round," Corell says. "As soon as they flip to a contemporary all high-capacity storage infrastructure, the trade at giant will likely be on that trajectory. Plus, we're beginning to see these classes realized on the worth of contemporary storage in AI utilized to different segments as properly, reminiscent of massive knowledge analytics, HPC, and plenty of extra."
Whereas all-flash options are being embraced virtually universally, there’ll at all times be a spot for HDDs, he provides. HDDs will persist in usages like archival, chilly storage, and situations the place pure value per gigabyte issues outweigh the necessity for real-time entry. However because the token financial system heats up and enterprises notice worth in monetizing knowledge, the nice and cozy and warming knowledge segments will proceed to develop.
Fixing energy challenges of the longer term
Now in its 4th era, with greater than 122 cumulative exabytes shipped thus far, Solidigm’s QLC (Quad-Degree Cell) know-how has led the trade in balancing larger drive capacities with value effectivity.
"We don’t consider storage as simply storing bits and bytes. We take into consideration how we are able to develop these superb drives which can be in a position to ship advantages at an answer degree," Corell says. "The shining star on that’s our not too long ago launched, E1.S, designed particularly for dense and environment friendly storage in direct connect storage configurations for the next-generation fanless GPU server."
The Solidigm D7-PS1010 E1.S is a breakthrough, the trade’s first eSSD with single-sided direct-to-chip liquid cooling know-how. Solidigm labored with NVIDIA to handle the twin challenges of warmth administration and value effectivity, whereas delivering the excessive efficiency required for demanding AI workloads.
"We’re quickly shifting to an surroundings the place all crucial IT elements will likely be direct-to-chip liquid-cooled on the direct connect facet," he says. "I feel the market must be taking a look at their strategy to cooling, as a result of energy limitations, energy challenges usually are not going to abate in my lifetime, at the very least. They must be making use of a neocloud mindset to how they’re architecting essentially the most environment friendly infrastructure."
More and more advanced inference is pushing in opposition to a reminiscence wall, which makes storage structure a front-line design problem, not an afterthought. Excessive-capacity SSDs, paired with liquid cooling and environment friendly design, are rising as the one path to satisfy AI’s escalating calls for. The mandate now’s to construct infrastructure not only for effectivity, however for storage that may effectively scale as knowledge grows. The organizations that realign storage now would be the ones in a position to scale AI tomorrow.
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