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Samsung HBM2 Aquabolt – 4GB

Samsung HBM2 Aquabolt – 4GB

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Samsung HBM2 Aquabolt – 4GB

High Bandwidth Memory for AI, HPC and Graphics Acceleration

Samsung HBM2 Aquabolt 4GB is a stacked high-bandwidth DRAM solution designed for advanced computing platforms including AI accelerators, GPUs, and high-performance computing (HPC) systems. Utilizing TSV (Through-Silicon Via) technology and wide I/O architecture, Aquabolt enables significantly higher bandwidth compared to conventional graphics memory architectures.

Each HBM2 stack supports up to 1024 I/O channels with data rates reaching 2.4Gbps per pin at 1.2V. In multi-stack configurations, system-level bandwidth can scale up to 1.2TB/s depending on platform design.

Technical Overview

  • Memory Type: HBM2 (High Bandwidth Memory)
  • Capacity: 4GB per stack
  • I/O Width: 1024-bit
  • Data Rate: Up to 2.4Gbps per pin
  • Voltage: 1.2V
  • Technology: TSV-based stacked DRAM
  • Target Applications: AI accelerators, GPUs, supercomputing platforms

Part Numbers

Model
KHA844801X-MC12
KHA844801X-MC13
KHA844801X-MN12
KHA844801X-MN13


Architecture & Reliability

Samsung HBM2 Aquabolt 4GB memory stack integrates advanced thermal bump structures and protective base layer design to improve mechanical robustness and thermal stability in high-density GPU environments.

For system designers searching for Samsung HBM2 Aquabolt 4GB stack, this solution provides high bandwidth memory for AI accelerators and GPU architectures requiring compact footprint and extreme data throughput.

FAQ

Q1: Is HBM2 Aquabolt a memory module?
No. HBM2 Aquabolt is a stacked DRAM package using TSV interconnect technology and is mounted directly onto an interposer or substrate in advanced GPU and accelerator designs.

Q2: What makes HBM2 different from GDDR memory?
HBM2 uses a wide I/O interface and stacked architecture to deliver higher bandwidth within a smaller physical footprint, optimized for high-performance computing workloads.

Q3: What applications use 4GB HBM2 stacks?
AI training accelerators, deep learning processors, high-end GPUs, and supercomputing systems.

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