330-BCFX Dell 94GB H100 NVL Tensor Core GPU Memory Interface

Details of Dell 94GB H100 Tensor Core GPU Interface

The Dell 330-BCFX GPU Memory Interface delivers exceptional performance for high-end computing workloads, featuring HBM3 memory, an expansive 6,016-bit memory bus, and PCI Express 5.0 x16 connectivity. Engineered for advanced AI, virtualization, and data-intensive applications, this GPU memory interface ensures maximum efficiency and reliability.

General Specifications

• Manufacturer: Dell
• Part Number: 330-BCFX
• Device Type: GPU Memory Interface

Technical Details

Total Board Power

• PCIe 16-pin Cable (450 W / 600 W Mode):
  • Maximum: 400 W (default)
  • Compliance Limit: 310 W
  • Minimum: 200 W
• PCIe 16-pin Cable (300 W Mode):
  • Maximum: 310 W (default)
  • Compliance Limit: 310 W
  • Minimum: 200 W

Cooling and Mechanical Design

• Thermal Solution: Passive cooling
• Form Factor: Full-height, full-length (FHFL), 10.5-inch, dual-slot

PCI Device Identifiers

• Device ID: 0x2321
• Vendor ID: 0x10de
• Sub-vendor ID: 0x10de
• Sub-system ID: 0x1839

GPU Clock Speeds

• Base Clock: 1,080 MHz
• Boost Clock: 1,785 MHz
• Performance State: P0

Firmware and BIOS

• EEPROM Size: 8 Mbit
• UEFI Support: Not supported

PCI Express Interface

• Gen5 x16, Gen5 x8, Gen4 x16 support
• Lane and polarity reversal supported

Multi-instance GPU & Security

• MIG (Multi-instance GPU): Up to 7 instances
• Secure Boot (CEC): Supported

Power Connectors

• One PCIe 16-pin auxiliary power connector (12V, 2x6)

Weight Details

• Board: 1,214 g (excluding bracket, extenders, bridges)
• NVLink Bridge: 20.5 g per bridge (x3 bridges)
• Bracket with Screws: 20 g
• Enhanced Straight Extender: 35 g
• Long Offset Extender: 48 g
• Straight Extender: 32 g

Memory Specifications

• Memory Clock: 2,619 MHz
• Memory Type: HBM3
• Memory Capacity: 94 GB
• Memory Bus Width: 6,016 bits
• Peak Memory Bandwidth: 3,938 GB/s

Software and Virtualization Support

SR-IOV Support

• Supported with 32 virtual functions (VFs)

BAR Address Allocation

• Physical Function:
  • BAR0: 16 MiB
  • BAR2: 128 GiB
  • BAR4: 32 MiB
• Virtual Function:
  • BAR0: 8 MiB (256 KiB per VF)
  • BAR1: 128 GiB, 64-bit (4 GiB per VF)
  • BAR3: 1 GiB, 64-bit (32 MiB per VF)

Interrupt and Forwarding Support

• MSI-X: Supported
• MSI: Not supported
• ARI Forwarding: Supported

Driver and CUDA Support

• Linux: R535 or later
• Windows: R535 or later
• NVIDIA CUDA: x86, CUDA 12.2 or later
• Virtual GPU Software: Supports vGPU 16.1 or later (NVIDIA Virtual Compute Server)
• NVIDIA AI Enterprise: Compatible with VMware

Additional Software & Certification

• NVIDIA-certified Systems: 2.8 or later
• Secure Boot: Supported
• CEC Firmware: Version 00.02.0134.0000 or later
• Nvflash Version: 5.816.0 or later

PCI Classification & ECC Support

• PCI Class Code: 0x03 – Display Controller
• PCI Subclass Code: 0x02 – 3D Controller
• ECC Support: Enabled

SMBus and IPMI Support

• SMBus 8-bit Address: 0x9E (write), 0x9F (read)
• IPMI FRU EEPROM I2C Address: 0x50 (7-bit), 0xA0 (8-bit)
• Reserved I2C Addresses: 0xAA, 0xAC, 0xA0
• SMBus Direct Access: Supported
• SMBPBI (SMBus Post-box Interface): Supported

Environmental and Reliability Specifications

Operating Conditions

• Ambient Operating Temperature: 0°C to 50°C
• Short-term Ambient Operating Temperature: -5°C to 55°C
• Operating Humidity: 5% to 85% RH
• Short-term Operating Humidity: 5% to 93% RH

Storage Conditions

• Storage Temperature: -40°C to 75°C
• Storage Humidity: 5% to 95% RH

Reliability Metrics

• Mean Time Between Failures (MTBF): TBD

Dell 330-BCFX Dell 94GB H100 GPU Memory Interface Overview

The Dell 330-BCFX GPU, equipped with 94GB of H100 NVL Tensor Core memory, represents the cutting edge of high-performance computing solutions for enterprises, research institutions, and advanced AI workloads. This GPU leverages a 6016-bit HBM3 memory interface and offers an unprecedented memory bandwidth of 3938GB/s, ensuring ultra-fast data processing for demanding computational tasks. Designed for PCI-E 5.0 x16 slots, this graphics card delivers scalable performance across multiple configurations, making it ideal for GPU-intensive operations such as AI model training, scientific simulations, and large-scale data analytics.

Advanced Memory Architecture

HBM3 Memory Interface

The HBM3 memory interface on the Dell 330-BCFX provides a significant performance boost over traditional memory architectures. With a 6016-bit memory bus, it allows for highly parallelized data transfer, reducing latency and increasing throughput for large datasets. This architecture is particularly advantageous in deep learning and neural network applications, where rapid access to memory can drastically reduce training times.

Tensor Core Memory Capabilities

The 94GB of Tensor Core memory enables exceptional computation for AI workloads. Tensor Cores accelerate matrix multiplication and convolution operations, which are fundamental to machine learning and deep learning processes. The combination of high memory capacity and specialized processing cores ensures that large models and datasets can be handled efficiently without the need for constant memory swapping, which typically slows down traditional GPUs.

PCI-E 5.0 x16 Interface and Bandwidth

High-Speed Data Transfer

The Dell 330-BCFX utilizes the PCI-E 5.0 x16 interface, providing a high-speed communication channel between the GPU and the host system. This interface supports double the data rate of PCI-E 4.0, facilitating faster data transfer for high-resolution simulations, real-time rendering, and AI inferencing tasks. The seamless interaction between the GPU and CPU ensures minimal bottlenecks in memory-intensive applications.

Bandwidth Optimization

With a memory bandwidth of 3938GB/s, this GPU is optimized for workloads that require continuous high-speed access to memory. Scientific computing, such as molecular modeling and climate simulations, benefits from this enhanced bandwidth by enabling larger datasets to be processed in real time. Additionally, the high bandwidth supports multi-GPU configurations, allowing organizations to scale their computing power without sacrificing performance.

Performance in AI and Deep Learning

Tensor Core Acceleration

The H100 NVL Tensor Cores embedded in the Dell 330-BCFX GPU provide accelerated performance for matrix and vector computations. These cores are specifically designed to optimize AI operations such as training large language models, reinforcement learning, and generative AI applications. The GPU’s architecture minimizes idle times and maximizes throughput, resulting in faster convergence of deep learning models.

Scalability for Enterprise AI

This GPU category is engineered to support enterprise-level AI environments. Organizations can deploy multiple Dell 330-BCFX GPUs in a single server to create highly parallelized processing nodes. Such configurations are essential for tasks that demand extreme computation, including AI research, predictive analytics, and large-scale simulations. The scalability ensures that businesses can meet growing computational requirements without extensive hardware redesigns.

Thermal Management and Reliability

Advanced Cooling Systems

The Dell 330-BCFX integrates sophisticated thermal management technologies to maintain optimal operating temperatures even under maximum load. Effective heat dissipation ensures consistent performance during extended periods of heavy computation, preventing thermal throttling that could otherwise limit efficiency. The advanced cooling mechanisms include high-performance fans and heat sinks specifically designed to accommodate the GPU’s high memory and core count.

Reliability for Continuous Operation

Enterprise-grade reliability is a hallmark of this GPU series. The Dell 330-BCFX is built to withstand continuous workloads with minimal risk of failure. Redundant power delivery and robust component quality provide stability for mission-critical applications, such as financial modeling, weather prediction, and AI inference in production environments. This ensures that organizations can rely on sustained performance without interruptions.

Software Ecosystem and Driver Support

Compatibility with AI Frameworks

The Dell 330-BCFX is fully compatible with leading AI frameworks, including TensorFlow, PyTorch, and CUDA-based applications. Optimized drivers and software stacks enable seamless integration into existing data centers, reducing deployment time and enhancing system performance. This compatibility ensures that organizations can leverage the GPU’s full potential for both training and inference tasks.

Enterprise Management Tools

Dell provides comprehensive management software to monitor and optimize GPU performance. Tools allow administrators to track temperature, power consumption, memory usage, and overall workload distribution. Such insights are critical for maximizing efficiency in high-performance computing clusters and ensuring that resources are allocated effectively across multiple GPU instances.

Use Cases and Application Areas

High-Performance Computing

The Dell 330-BCFX is ideally suited for high-performance computing (HPC) environments where computational speed and memory capacity are paramount. Applications include scientific research simulations, engineering modeling, and computational fluid dynamics. The combination of high memory bandwidth, Tensor Core acceleration, and PCI-E 5.0 support ensures that HPC tasks are executed with maximum efficiency.

Artificial Intelligence and Machine Learning

AI and machine learning workloads benefit greatly from the GPU’s Tensor Core design. Large neural networks, natural language processing models, and computer vision tasks can be trained and deployed faster than ever before. The GPU’s large memory and bandwidth capacity allow researchers and enterprises to work with datasets of unprecedented size, improving model accuracy and reducing time-to-insight.

Data Analytics and Scientific Simulation

For organizations that rely on big data analytics, the Dell 330-BCFX provides the computational power needed to process and analyze vast amounts of information quickly. In scientific research, the GPU accelerates simulations in areas such as genomics, molecular dynamics, and climate modeling. This enables faster results and more precise predictions, facilitating breakthroughs in research and innovation.

Expansion and Integration Options

Multi-GPU Configurations

The PCI-E 5.0 x16 interface and high-bandwidth memory make the Dell 330-BCFX highly suitable for multi-GPU setups. Data centers can integrate several GPUs in a single server chassis, significantly increasing parallel computing power. This capability is particularly important for AI research institutions and large enterprises running complex simulations or handling extensive AI workloads.

Compatibility with Dell Enterprise Servers

This GPU is optimized for integration with Dell PowerEdge servers, ensuring seamless compatibility with enterprise hardware. The combination of advanced memory architecture, PCI-E 5.0 connectivity, and Dell’s server ecosystem guarantees that organizations can maximize the GPU’s capabilities without extensive hardware modifications. Such integration supports efficient deployment and scalable expansion.