The standard supports bump pitches greater than 90 µm and channel reaches up to 20 mm, which are two features that enable dropping the expensive interposer and using less-expensive organic substrate routing. However, getting rid of the interposer and CoWoS (or similar) packaging does not automatically make SPHBM4 inexpensive. SPHBM4 still requires massive HBM4 DRAM ICs, 2.5D packaging, a complex base die (which is likely costlier than the one used by conventional HBM4), and advanced package assembly with through-silicon vias. In addition, SPHBM4's narrow interface consumes significantly less die perimeter and silicon area inside processors, which makes it more attractive to companies that strive to install more compute capability and/or intend to install more memory stacks around their processors. However, we are still talking about a niche high-performance memory technology that will address select applications and will barely rival HBM4 directly.
When it comes to maximum performance, HBM4 moves the data at 8 GT/s (though most controllers and chips support higher data rates), so one HBM4 stack can offer bandwidth of 2 TB/s. HBM4E is set to up data transfer rate to 12 – 12.8 GT/s, therefore increasing peak bandwidth to 3 – 3.3 TB/s per stack. By contrast, one SPHBM4 with a 46 GT/s interface can hit 2.944 TB/s, though do not expect the initial versions of SPHBM4 to hit the maximum speed. Therefore, it is likely that HBM4, HBM4E, and C-HBM4E will maintain a performance lead in terms of bandwidth over SPHBM4 in the foreseeable future.
HBM4 latency will still probably have an edge over SPHBM4. HBM4 essentially connects to its host processor almost directly through a very simple interface. By contrast, SPHBM4 inserts a much more sophisticated PHY that performs serialization/deserialization, lane training, FEC handling, and other operations that can add a few nanoseconds of latency. This may not be a big problem for some applications, but inference benefits a lot from low latencies.
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When it comes to power and voltages, HBM4 and SPHBM4 share the same DRAM core voltage because SPHBM4 reuses standard HBM4 DRAM stacks. However, I/O is different: HBM4 leaves the interface voltage up to memory vendors and allows implementations at 0.7V, 0.75V, 0.8V, or 0.9V, depending on the desired balance between power, speed, and signal integrity. By contrast, SPHBM4 standardizes the external I/O at 0.75V.
Also, HBM4 moves data over a very wide interface with many slow parallel links that tend to be very energy efficient. By contrast, SPHBM4 moves the same amount of data through one-quarter as many wires, which run roughly four times faster. High-speed data transfer tends to be less energy efficient than 'slow' data transfers over a wide interface. Keeping in mind SPHBM4's rather sophisticated PHY that converts a wide interface into a narrow interface, which is likely a power-hungry process. Nonetheless, the 4X lower number of drivers and receivers could tangibly reduce the power consumption of SPHBM4. That said, without implementation details from DRAM makers or a processor developer, it is impossible to conclude which memory type has lower power consumption.
Last but not least, SPHBM4 essentially trades manufacturing challenges that arise from using silicon interposers for an engineering challenge of developing an extremely sophisticated base die/PHY. Developing and manufacturing such a base die should not be a problem for foundries. However, it remains to be seen whether DRAM makers can design and produce SPHBM4 with decent power efficiency. After all, both Micron and SK hynix work with TSMC to build C-HBM4E and HBM4E base dies, whereas Samsung's memory division uses base dies produced by Samsung Foundry.
One interesting aspect of SPHBM4 is whether Chinese developers of AI accelerators can benefit from this technology. In theory, Chinese developers like Biren, Huawei, Moore Threads, and other blacklisted companies that cannot use TSMC's chip manufacturing or packaging services could become one of the biggest beneficiaries of SPHBM4, perhaps even more so than the U.S.
First up, a smaller shoreline directly benefits chips that are made using trailing nodes, as it enables packing more compute capability into them without sacrificing memory bandwidth or capacity. Secondly, Chinese OSATs currently do not offer CoWoS-like technologies, so eliminating the interposer and using advanced organic substrates is a benefit.
However, SPHBM4 still requires HBM4 DRAM stacks, and today, Samsung, SK hynix, and Micron are the only companies capable of producing them, while China-based CXMT can barely make HBM2E. Furthermore, building a 46 GT/s PHY is very hard and will likely be challenging for Chinese IC developers.
Nonetheless, assembling SPHBM4 packages on organic substrates is arguably more aligned with China's existing manufacturing base, so if local DRAM makers eventually develop competitive HBM4-class memory, SPHBM4 could substantially reduce one of the country's remaining infrastructure gaps.
JEDEC's SPHBM4 looks like a promising standard that can potentially address a broader range of applications than HBM4 itself due to lower integration cost. Still, HBM4, HBM4E, and C-HBM4E will maintain performance leadership, which will make them a preferable choice for flagship AI accelerators in the coming years.
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Anton Shilov is a contributing writer at Tom\u2019s Hardware. Over the past couple of decades, he has covered everything from CPUs and GPUs to supercomputers and from modern process technologies and latest fab tools to high-tech industry trends. ","collapsible":{"enabled":true,"maxHeight":250,"readMoreText":"Read more","readLessText":"Read less"}}), "https://slice.vanilla.futurecdn.net/13-4-25/js/authorBio.js"); } else { console.error('%c FTE ','background: #9306F9; color: #ffffff','no lazy slice hydration function available'); } Anton Shilov Social Links Navigation Contributing Writer Anton Shilov is a contributing writer at Tom’s Hardware. Over the past couple of decades, he has covered everything from CPUs and GPUs to supercomputers and from modern process technologies and latest fab tools to high-tech industry trends.
Faiakes Would this be of use to GPUs or it too expensive? Reply
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- https://www.tomshardware.com/pc-components/dram/jedec-releases-new-sphbm4-standard-to-slash-ai-memory-costs-narrow-512-bit-interface-enables-dropping-expensive-interposers-for-organic-substrates#main
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