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773 pcs
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773 pcs | On Request | 1 | On Request | On Request | On Request | On Request | On Request |
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The HBM2X1M is a cutting-edge memory technology engineered for applications demanding exceptional bandwidth and minimal latency. Its primary advantage lies in its ability to dramatically accelerate data processing in graphics cards and high-speed computing systems.
Utilizing 3D stacking technology with Through-Silicon Vias (TSV), HBM2X1M minimizes signal transmission distances, leading to reduced latency. A key feature is its wide bus design, typically 1024 bits or wider, which provides several times the bandwidth of conventional memory interfaces. This makes it ideal for parallel data processing tasks.
With a typical bandwidth exceeding 1TB/s, HBM2X1M excels in demanding applications like graphics rendering and scientific computations. Furthermore, its energy efficiency is superior to GDDR memory, consuming less power per unit of data transferred, which is crucial for power-sensitive devices and data centers.
HBM2X1M finds extensive use in high-end graphics cards and is a staple in supercomputers and AI accelerators, enhancing computational efficiency in platforms like Google's TPU and IBM's PowerAI.
| Qty | Low | High |
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| 1+ | $3.00 | $3.00 |
Estimated market price range - modelled values for guidance only, not live distributor offers.
The bandwidth of HBM2X1M is typically 1TB/s or more.
HBM2X1M typically features a 1024-bit or wider interface.
HBM2X1M offers lower power consumption compared to GDDR memory.
HBM2X1M should be kept below 85°C.
HBM2X1M offers higher bandwidth and lower power consumption than GDDR6, but at a higher cost. GDDR6 is more suitable for cost-sensitive applications, while HBM2X1M is for high-performance computing.
Under normal usage conditions, HBM2X1M can last 5-10 years. However, high temperatures and overvoltage can significantly shorten its lifespan.
Some high-end models of HBM2X1M support ECC (Error Correction Code) to enhance data reliability, making them suitable for critical applications.