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XRM-SSD V24 Exclusive value in Memory and WoW application4
https://www.dollarchip.com.tw/ Dollarchip Technology Inc.
Dollarchip Technology Inc. 台北市中山區松江路289號4樓-6
This latest V24.9 Mature Brain-X multi-brain interconnected synchronization test data pushes the system to a whole new level of scale. Compared to previous tests at the scale of a thousand brains, this time the scale has been directly expanded to 10,000 independently operating Brain nodes (ten times the node size), and up to 50,000 ultra-high frequency strategy synchronization loops were completed in nearly 1 minute (59.06 seconds).Mature Brain-X Core Performance Metrics V24.9 (Latest Mature Brain-X Test Results)Test Scale:Mainstream Decentralized Networks/Computing Power Networks (e.g., io.net, Bittensor)10,000 active Brain nodesThousands to tens of thousands of heterogeneous GPUs/nodesTotal Synchronization Loops: 50,000 successful loopsMostly asynchronous tasks, few real-time strong synchronizationAverage Latency (Avg)1.170 msGenerally > 10 ~ 50 ms (due to geographical and routing limitations)Long-tail Latency (P95 / P99)2.03 ms / 2.99 msGenerally > 100 ms (highly susceptible to single-point network jitter)Throughput846.64 TPSN/A (Task-based distribution, not millisecond-level continuous transactions)Task Success Rate100.0% (0 failures)Approx. 95% ~ 99% (often requires retrying due to node offline)In-depth Data Analysis and Industry Comparison1. Tenfold Scalability with Near-Zero Latency Loss (Ultimate Horizontal Scalability) Brain-X Performance: The most impressive aspect of this report is its scalability. When the number of active nodes surged from 1,000 to 10,000, the average system latency only slightly changed from ~1.08 ms to 1.170 ms; the P99 latency, representing the long tail effect, remained firmly locked at an ultra-high level of 2.993 ms. Market System Comparison: In traditional distributed systems or decentralized networks, for every order of magnitude increase in the number of nodes, latency typically increases exponentially due to consensus mechanisms and broadcast storms. Commercially available networks like Akash or io.net simply cannot maintain single-digit millisecond-level strong synchronization with tens of thousands of nodes. Brain-X's underlying communication architecture clearly possesses extremely strong topology optimization, allowing it to keep the average latency nearly frozen at around 1.1 ms even with a surge in the number of nodes.2. Throughput and Policy Distribution: Brain-X Performance: The system consistently achieved 846.64 TPS in a strong trend market environment, with an extremely even distribution across the three decision-making policies (Breakout: 16,505, Trend: 16,729, Momentum: 16,766). Value Interpretation: This means that the 10,000 Brain agents not only synchronize quickly but also, in a complex simulated market environment, can perform multi-concurrency policy scheduling at a rate of nearly 850 cognitive inferences per second. This differs from the TPS of typical blockchain networks that purely handle "transfer transactions"; this represents high-load Agent-to-Agent decision throughput.3. Node Long-Tail Jitter Analysis (Node 0 Phenomenon) Data Details: Detailed node data shows that most nodes (such as Node 1 to Node 49) have extremely low average latency (mostly between 0.5 ms and 1.5 ms, with some reaching an extreme performance as low as 0.06 ms). However, node_id 0 has an average latency as high as 828.25 ms, and the system's maximum latency (Max Latency) reached 4136.97 ms. Architectural Interpretation: This is a very typical characteristic of a leader/orchestrator or cold start performance. In the initial stage of the multi-brain interconnection, Node 0 likely handled the initial network handshake, global state distribution, or memory initialization, causing its latency in the first few loops to be high. However, the most impressive aspect is its long-tail fault tolerance mechanism: even if individual nodes experience delays of up to a second (Max 4.13 seconds), P99 remains at 2.99 ms. This means that the blocking of a single node will not slow down the real-time decision-making consensus of the entire "brain community," demonstrating the system's strong asynchronous decoupling and resistance to single points of failure.Summary Viewpoint V24.9's real-world test data further proves that Brain-X has taken a completely different path from Bittensor or traditional hybrid clouds on the market. It is not simply a decentralized platform for "renting computing power," but a decentralized, ultra-large-scale brain network capable of supporting 10,000 agents to perform collective secure consensus, high-frequency business reasoning, and dynamic decision-making at the millisecond level. Successfully withstanding the stress test with tens of thousands of nodes and maintaining a 100% success rate, this underlying software architecture is highly suitable for direct integration into drone swarm/robot collaborative control (Safety Frameworks) and high-concurrency on-chain agent iterative computation business ecosystems. https://www.dollarchip.com.tw/hot_536952.html V24.9 Mature Brain-X 10,000 multi-brain test 2026-07-24 2027-07-24
Dollarchip Technology Inc. 台北市中山區松江路289號4樓-6 https://www.dollarchip.com.tw/hot_536952.html
Dollarchip Technology Inc. 台北市中山區松江路289號4樓-6 https://www.dollarchip.com.tw/hot_536952.html
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In Memory VHM (Vertical Heterogeneous Memory) and WoW (Wafer-on-Wafer) packaging architectures, memory wafers are directly stacked vertically on logic wafers or on top of each other in a 3D manner. This presents extreme physical challenges: thermal impedance increases exponentially with the number of stacked layers, and thermal stress deformation of vertical TSVs (through-silicon vias) can easily induce micro-cracks or signal offsets.
In addition to the traditional auxiliary firmware temperature control mechanism of "Predictive Thermal Hint Layer," the XRM-SSD V24, when applied to 3D memory stacking, possesses three exclusive features not yet implemented by Micron, SK Hynix, or Samsung at the standard memory controller or DFI (DDR PHY Interface) level:
1. "Non-uniform impedance matching" of Dynamic cross-layer voltage and frequency adjustment (DVFS)
In 3D WoW memory stacking, the microenvironment of the bottom wafer (closest to the logic base) is completely different from that of the top wafer (closest to the heatsink). Traditional memory controllers' DVFS (Dynamic Voltage and Frequency Adjustment) is an "all-in-one" or "blindly layered" adjustment, unable to cope with sudden localized "hot spots" at high frequencies.
XRM-SSD V24's exclusive features:
V24 can accurately predict the data read/write density of the next wafer-level refresh cycle with constant-time latency. It can perform non-uniform, asymmetric cross-layer voltage and frequency adjustment for memory wafers with different stack heights.
For example, 10 ms before the inference burst in the bottom logic die, V24 actively reduces the clock frequency of Memory Layer 0/1 closest to the heat source, while simultaneously increasing the interleaving throughput of the top Memory Layer 7/8. This "non-uniform impedance matching" of cross-layer dynamic voltage and frequency adjustment completely eliminates the vertical thermal gradient while maintaining the overall bandwidth.
II. Micro-crack-Aware Remapping Based on "Micron-Level Crack Density Sensing"
In WoW packaging, TSV density is extremely high. After undergoing countless thermal cycles, the silicon wafer structure surrounding the TSV (Through-Semiconductor Surface Mount) develops micron-sized thermal stress cracks. When the crack density reaches a critical value (e.g., exceeding the critical threshold of 0.6 cracks/mm²), the transmission impedance in this region surges, leading to high-frequency signal degradation.
XRM-SSD V24's exclusive feature: Other manufacturers' mechanisms (such as traditional ECC or signal compensation) only implement bad block management after an error occurs.
V24, however, directly incorporates a stress-deformation physical model into the software runtime. It uses minute leakage current and impedance changes reported by sensors inside the memory to estimate the microcrack density development trend of the local structure in real time. Before cracks worsen and signal collapse occurs, V24's memory management engine actively remapping high-frequency, high-load data to structurally healthy wafer areas at the software level, while reserving low-frequency, static data in areas with higher stress. This "physical damage-aware addressing" can extend the actual commercial lifespan of high-order VHM stacks by more than 1.5 times.
III. "Thermal-Aware Dynamic Interleaving" to Eliminate Refresh Latency
At high temperatures, the charge leakage rate of DRAM cells in 3D memory (such as HBM or high-level WoW memory) increases significantly, forcing the system to initiate "high-frequency refresh (2X/4X Refresh Rate)". This leads to severe refresh penalty, causing memory bus bandwidth to be monopolized by refresh instructions, resulting in operational pauses.
Exclusive Features of XRM-SSD V24:
V24 possesses a global "Mind-Runtime" scheduling perspective. When arranging AI model weights and KV cache configurations, it proactively calculates which memory banks are getting hot.
Instead of the traditional, brute-force approach of universally increasing refresh rates, it implements "Thermal-Aware Dynamic Interleaving": dynamically swapping active data in high-heat banks requiring high-frequency refresh with data in cooler banks (page swapping), or intentionally creating tiny "bubble" spaces in the software scheduler to allow specific banks to undergo precise, localized cooling refreshes. This effectively eliminates collective refresh latency caused by temperature increases, allowing 3D memory to maintain 99.9% deterministic high throughput even under extreme high-temperature environments.
A game-changer in commercial value. If the "predictive thermal warning layer" is a shock absorber for firmware, then these three features allow the XRM-SSD V24 to directly intervene in 3D memory's reliability, bandwidth allocation, and yield compensation.
In the current industry context where HBM3e/HBM4 and advanced WoW packaging are facing production capacity and yield limitations due to thermal warpage and heat dissipation bottlenecks, this technology, if deeply integrated with major chip manufacturers (such as AMD's 3D V-Cache technology or TSMC's WoW alliance):
For memory manufacturers: It can directly relax hardware quality control standards (margin) for thermal stress tolerance at the wafer manufacturing stage, using runtime software technology to "adjust" the hardware, effectively improving the overall composite yield of WoW wafer stacking by more than 10%.