ZeroPoint Applied sciences AB at the moment introduced a breakthrough hardware-accelerated reminiscence optimization product that permits the almost instantaneous compression and decompression of deployed foundational fashions, together with the main massive language fashions (LLMs).
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The brand new product, AI-MX, will likely be delivered to preliminary prospects and companions within the second half of 2025 and can allow enterprise and hyperscale datacenters to appreciate a 1.5 instances improve in addressable reminiscence, reminiscence bandwidth, and tokens served per second for functions that depend on massive foundational fashions. The complete technical specs of AI-MX can be found right here.
“Foundational fashions are stretching the bounds of even essentially the most refined datacenter infrastructures. Demand for reminiscence capability, energy, and bandwidth continues to increase quarter-upon-quarter,” mentioned Klas Moreau, CEO of ZeroPoint Applied sciences. “With at the moment’s announcement, we introduce a first-of-its-kind reminiscence optimization resolution that has the potential to avoid wasting corporations billions of {dollars} per yr associated to constructing and working large-scale datacenters for AI functions.”
“Futurum Intelligence presently predicts the overall AI software program and instruments market to achieve a worth of $440B by 2029 and Signal65 believes that ZeroPoint is positioned to handle a key problem inside this fast-growing market with AI-MX,” mentioned Mitch Lewis, Efficiency Analyst at Signal65. “Signal65 believes that AI-MX is presently a novel providing and that with ongoing improvement and alignment with main know-how companions, there’s robust progress alternative for each ZeroPoint and AI-MX.”
ZeroPoint’s proprietary hardware-accelerated compression, compaction, and reminiscence administration applied sciences function at low nanosecond latencies, enabling them to work greater than 1000 instances sooner than extra conventional compression algorithms.
For foundational mannequin workloads, AI-MX permits enterprise and hyperscale datacenters to extend the addressable capability and bandwidth of their current reminiscence by 1.5 instances, whereas concurrently gaining a big improve in efficiency per watt. Critically, the brand new AI-MX product works throughout a broad number of reminiscence varieties, together with HBM, LPDDR, GDDR and DDR – making certain that the reminiscence optimization advantages apply to almost each potential AI acceleration use case.
A abstract of the advantages supplied by the preliminary model of AI-MX embody:
Expands efficient reminiscence capability by as much as 50%
- This enables end-users to retailer AI mannequin information extra effectively. For instance, enabling 150GB of mannequin information to suit inside 100GB of HBM capability.
Enhances AI accelerator capability
- An AI accelerator with 4 HBM stacks and AI-MX can function as if it has the capability of 6 HBM stacks.
Improves efficient reminiscence bandwidth
- Obtain an identical 1.5 instances enchancment in bandwidth effectivity by transferring extra mannequin information per transaction.
The above advantages are particularly related to the preliminary implementation of the AI-MX product. ZeroPoint Applied sciences goals to additional exceed the 1.5 instances will increase to capability and efficiency in subsequent generations of the AI-MX product.
Given the exponentially rising reminiscence calls for of at the moment’s functions, partially pushed by the explosive progress of generative AI, ZeroPoint addresses the vital want of at the moment’s hyperscale and enterprise information middle operators to get essentially the most efficiency and capability potential from more and more costly and power-hungry reminiscence.
For extra normal use circumstances (these not associated to foundational fashions) ZeroPoint’s options are confirmed to extend normal reminiscence capability by 2-4x whereas additionally delivering as much as 50% extra efficiency per watt. Together, these two results can cut back the overall price of possession of hyperscale information middle servers by as much as 25%.
ZeroPoint provides reminiscence optimization options throughout the whole reminiscence hierarchy – all the best way from cache to storage. ZeroPoint’s know-how is agnostic to information load, processor kind, architectures, reminiscence applied sciences and processing node, and the corporate’s IP has already been confirmed on a TSMC 5nm node.
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