#highbandwidthflash — Public Fediverse posts

🚫💾🚫 Ah yes, the enlightening discourse on High-Bandwidth Flash where readers are treated to a riveting display of the 403 Forbidden error page. Who needs efficient storage for model weights when you can have a masterclass in denial of access? 🙄 #InnovationAtItsFinest
https://spectrum.ieee.org/high-bandwidth-flash #HighBandwidthFlash #403Forbidden #ErrorPage #StorageInnovation #DenialOfAccess #HackerNews #ngated

High-Bandwidth Flash offers efficient storage for model weights

https://spectrum.ieee.org/high-bandwidth-flash

Comments: https://news.ycombinator.com/item?id=48915393

#HackerNews #HighBandwidthFlash #efficientStorage #modelWeights #storageSolutions #techInnovation

Dentro la gerarchia della memoria delle GPU: come i server AI spostano i dati dagli SSD alla HBM

Ti sei mai chiesto come i modelli di intelligenza artificiale trasferiscono i dati alla GPU? Questo articolo spiega in modo semplice i diversi livelli di memoria all'interno di un server AI, perché la memoria della GPU è diventata un collo di bottiglia e quali nuove tecnologie potrebbero migliorare le prestazioni dell'intelligenza artificiale.

buysellram.com/blog/inside-the…

#HBM #HBM4 #GPUMemory #AIInfrastructure #DataCenter #CXL #HighBandwidthFlash #AIHardware #MemoryHierarchy #AIInference #NVMe #ITAD

Why can't a GPU just carry more HBM? Interposers max out in size, stacking 12 to 16 DRAM dies compounds yield losses, and every stack sits beside a kilowatt-class package that hates sharing heat. So capacity climbs in careful steps — 80 GB on the H100, 141 on the H200, 192 on the B200, 288 on Blackwell Ultra — while KV caches for long-context inference balloon past 40 GB per request.

That gap between what models demand and what packaging permits is reshaping server design. NVIDIA's Rubin platform treats CPU memory and HBM as one coherent pool. SanDisk and SK hynix are standardizing High Bandwidth Flash as a capacity tier under HBM, with first samples due this half. CXL 4.0 pooling hardware is landing in racks now.

This article walks the whole memory hierarchy, from on-chip SRAM to NVMe, and explains what each emerging technology actually solves — and what it doesn't.

https://www.buysellram.com/blog/inside-the-gpu-memory-hierarchy-how-ai-servers-move-data-from-ssd-to-hbm/

#HBM #HBM4 #GPUMemory #AIInfrastructure #DataCenter #CXL #HighBandwidthFlash #AIHardware #MemoryHierarchy #AIInference #NVMe #ITAD #technology

A modern AI server runs five layers of memory, from nanosecond on-chip SRAM to petabyte-scale SSDs, and keeping the GPU fed is the whole engineering game. This piece walks the full hierarchy: why HBM became the bottleneck, why adding more isn't simple, and where HBF, CXL, and PIM fit into the next generation.

https://www.buysellram.com/blog/inside-the-gpu-memory-hierarchy-how-ai-servers-move-data-from-ssd-to-hbm/

#HBM #HBM4 #GPUMemory #AIInfrastructure #DataCenter #CXL #HighBandwidthFlash #AIHardware #MemoryHierarchy #AIInference #NVMe #tech

Running AI in production? A lot of the bill is memory. Every token a model generates is served from fast memory next to the GPU — and that memory, HBM, is scarce and expensive.
HBF is built to attack that cost: much of HBM's bandwidth at a fraction of the price per GB. A new explainer covers what HBF is, how it could lower inference costs, and how close it actually is.

https://www.buysellram.com/blog/high-bandwidth-flash-ai-inference-cost/

#HBF #HighBandwidthFlash #AIinference #HBM #AImemory #GPU #DataCenter #NAND #SanDisk #MemoryWall

SK hynix and Sandisk want HBF to become the missing memory layer for AI inference

https://fed.brid.gy/r/https://nerds.xyz/2026/02/sk-hynix-sandisk-hbf-ai-inference-memory/