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CSM
ProShares Large Cap Core Plus
stock BATS ETF

At Close
Aug 5, 2026 9:48:46 AM EDT
89.77USD+0.526%(+0.47)2,510
62.47Bid   2147.48Ask   2085.01Spread
Pre-market
0.00USD-100.000%(-87.72)0
After-hours
Aug 5, 2026 4:10:30 PM EDT
89.10USD-0.748%(-0.67)1
OverviewOption ChainMax PainOptionsPrice & VolumeSplitsDividendsHistoricalExchange VolumeDark Pool LevelsDark Pool PrintsExchangesShort VolumeShort Interest - DailyShort InterestBorrow Fee (CTB)Failure to Deliver (FTD)ShortsTrendsNewsTrends
CSM Reddit Mentions
Subreddits
Limit Labels     

We have sentiment values and mention counts going back to 2017. The complete data set is available via the API.
Take me to the API
CSM Specific Mentions
As of Aug 5, 2026 7:47:02 PM EDT (<1 min. ago)
Includes all comments and posts. Mentions per user per ticker capped at one per hour.
36 days ago • u/Charuru • r/NVDA_Stock • etched_is_here_with_a_product • C
> Introducing Cluster-Scale Memory (CSM) for low latency workloads.
>
> Today's AI chips using HBM can’t achieve SRAM-level decode speeds due to memory subsystem and interconnect bottlenecks. SRAM-only chips have lower FLOPs density and memory capacity, sacrificing throughput.
>
> You’re forced to make a tradeoff: serve at much slower speeds, or run at low batch sizes and suffer from higher costs.
>
> When running large MoE models, token routing across experts requires sending data through a deep memory hierarchy and a networking switch to reach a destination expert.
>
> Each memory layer inherently adds latency; thus, the best layer is no layer.
>
> We’ve designed a new architecture that creates a shared low-latency memory pool across the entire scale-up domain.
>
> We use a proprietary ultra-low-latency, high-bandwidth interconnect to enable dramatically faster memory access across chips.
>
> Our HBM/SRAM hybrid design solves both memory capacity and mem2mem latency, enabling high throughput and interactivity simultaneously.
>
> CSM improves latency and avoids today's cost, reliability, yield, thermal, and compute tradeoffs of SRAM-only chips, 3D DRAM chips, or optics.
Fascinating stuff, I argued many moons ago about the need for a new type of memory in between HBM and SRAM, well it looks like someone has done it. Too bad it's not Nvidia.
https://www.reddit.com/r/NVDA_Stock/comments/1l0c3qt/nvidia_needs_to_make_an_ultralow_latency/
sentiment -0.34
36 days ago • u/Charuru • r/NVDA_Stock • etched_is_here_with_a_product • C
> Introducing Cluster-Scale Memory (CSM) for low latency workloads.
>
> Today's AI chips using HBM can’t achieve SRAM-level decode speeds due to memory subsystem and interconnect bottlenecks. SRAM-only chips have lower FLOPs density and memory capacity, sacrificing throughput.
>
> You’re forced to make a tradeoff: serve at much slower speeds, or run at low batch sizes and suffer from higher costs.
>
> When running large MoE models, token routing across experts requires sending data through a deep memory hierarchy and a networking switch to reach a destination expert.
>
> Each memory layer inherently adds latency; thus, the best layer is no layer.
>
> We’ve designed a new architecture that creates a shared low-latency memory pool across the entire scale-up domain.
>
> We use a proprietary ultra-low-latency, high-bandwidth interconnect to enable dramatically faster memory access across chips.
>
> Our HBM/SRAM hybrid design solves both memory capacity and mem2mem latency, enabling high throughput and interactivity simultaneously.
>
> CSM improves latency and avoids today's cost, reliability, yield, thermal, and compute tradeoffs of SRAM-only chips, 3D DRAM chips, or optics.
Fascinating stuff, I argued many moons ago about the need for a new type of memory in between HBM and SRAM, well it looks like someone has done it. Too bad it's not Nvidia.
https://www.reddit.com/r/NVDA_Stock/comments/1l0c3qt/nvidia_needs_to_make_an_ultralow_latency/
sentiment -0.34


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