575TK Dell 300W 80GB PCIE Double Wide Full Height GPU

Specification of Dell 575TK 300W PCIE GPU

The Dell 575TK is a high-performance 300-watt graphics accelerator featuring the Nvidia Ampere A100 chipset. Designed for enterprise-grade computing, this dual-slot, full-height PCIe card delivers exceptional processing power for data centers and AI workloads.

Brand Details

• Brand: Dell
• Model Identifier: 575TK
• Hardware Category: GPU Accelerator

Advanced Specifications

Memory and Bandwidth

• Video Memory: 80GB HBM2e
• Bus Width: 5120-bit
• Data Throughput: Up to 1.94 Terabytes per second

Connectivity and Form Factor

• Interface Type: PCI Express 4.0 x16
• Card Dimensions: Full-Height, Dual-Wide (two-slot)
• Cooling Mechanism: Passive thermal design for server airflow optimization

Power and Performance

• Thermal Design Power (TDP): 300 Watts
• Power Input: Requires 1x 8-pin EPS connector
• CUDA Processing Units: 6912 cores
• Tensor Units: 432 (3rd Gen)
• Video Outputs: None (optimized for compute tasks)
• Multi-Instance GPU (MIG): Capable of splitting into up to 7 isolated GPU partitions

Server Compatibility

Supported Rack Servers

• Dell PowerEdge R750
• Dell PowerEdge R750xa
• Dell PowerEdge R7525 (PCIe variant)
• Dell PowerEdge R740
• Dell PowerEdge R740xd
• Dell PowerEdge R760
• Dell PowerEdge R760xa
• Dell PowerEdge R7615
• Dell PowerEdge R7625
• Dell PowerEdge R840
• Dell PowerEdge R940xa

Supported Tower Servers

• Dell PowerEdge T430
• Dell PowerEdge T440
• Dell PowerEdge T630
• Dell PowerEdge T640

Supported Edge Servers

• Dell PowerEdge XR12
• Dell PowerEdge XR7620

Dell 575TK 300W 80GB PCIE Full Height GPU Overview

The Dell 575TK 300W 80GB Nvidia Ampere A100 PCIe Passive Double Wide Full Height GPU represents one of the most advanced computing accelerators designed for high-performance computing (HPC), artificial intelligence (AI), and data analytics workloads. Built upon Nvidia’s powerful Ampere architecture, this GPU is tailored for Dell PowerEdge servers and other enterprise-class systems requiring uncompromising performance and energy efficiency. Its 80GB HBM2e memory ensures extremely high bandwidth for complex computational tasks, while the 300W thermal design power (TDP) maintains optimal balance between power and cooling efficiency. This model’s passive cooling design makes it suitable for data center environments where airflow and thermal control are managed at the chassis level.

Advanced Ampere Architecture

At the heart of the Dell 575TK GPU lies Nvidia’s Ampere architecture, which delivers a generational leap in both efficiency and performance. The architecture integrates third-generation Tensor Cores and second-generation RT Cores, designed to accelerate AI inference, training, and real-time ray tracing. It leverages CUDA cores for massive parallel processing, providing computational flexibility across diverse workloads. With 80GB of ultra-fast HBM2e memory and an enormous memory bandwidth of up to 2TB/s, it offers exceptional throughput for deep learning models, data-intensive simulations, and scientific visualization.

Innovative Design and PCIe Interface

The Dell 575TK GPU uses a PCI Express Gen4 x16 interface, enabling faster communication between the GPU and system CPU. This interface doubles the data throughput compared to PCIe Gen3, reducing latency and maximizing the performance of GPU-driven workloads. The double-wide form factor ensures proper space for power delivery and thermal dissipation, while the full-height bracket design allows easy installation in standard enterprise-grade servers. The passive cooling system integrates seamlessly with rack-mounted systems, relying on optimized chassis airflow to maintain temperature stability.

Enhanced Compute Capability for AI and HPC

The Nvidia Ampere A100 GPU embedded in the Dell 575TK delivers unparalleled compute density. It supports both FP64 and Tensor Float 32 (TF32) precision modes, optimizing scientific and AI workloads. With support for mixed-precision computing, researchers and engineers can accelerate simulations, neural network training, and predictive modeling. The architecture allows automatic adjustment of precision levels to achieve faster computation without compromising accuracy. Furthermore, the inclusion of Multi-Instance GPU (MIG) technology enables a single A100 GPU to be partitioned into multiple independent instances, offering flexibility for multi-tenant or multi-user environments.

Multi-Instance GPU Technology

MIG technology revolutionizes GPU utilization by allowing up to seven GPU instances per physical device. Each instance behaves like a separate GPU, complete with its own compute, memory, and cache resources. This partitioning enhances the ability of data centers to share resources efficiently across diverse workloads. Administrators can run simultaneous applications with guaranteed quality of service (QoS), making the Dell 575TK a versatile option for cloud environments, containerized workloads, and virtualized infrastructures. Whether used for AI inference, model training, or large-scale data processing, MIG ensures predictable performance across all running tasks.

Scalability in Data Center Environments

Designed for demanding enterprise and scientific workloads, the Dell 575TK 300W A100 GPU delivers unmatched scalability and computational throughput. It supports large-scale deployment configurations, where multiple GPUs can be interconnected via high-speed Nvidia NVLink bridges. This allows direct GPU-to-GPU communication, drastically reducing the need to route data through the CPU. The combination of NVLink and PCIe Gen4 provides superior bandwidth, ensuring data flows efficiently within AI clusters or HPC systems.

High Bandwidth Memory for Intensive Workloads

Equipped with 80GB of high-bandwidth memory (HBM2e), this GPU offers exceptional data transfer speeds and low latency. Each memory stack is engineered to handle massive datasets used in machine learning and analytics. This allows for efficient manipulation of large matrices, neural network parameters, and scientific simulation data. The 80GB capacity ensures headroom for large models without the need for frequent memory swapping, significantly improving throughput and reducing computational overhead. The result is a GPU capable of supporting enterprise AI frameworks such as TensorFlow, PyTorch, and MXNet with remarkable efficiency.

Energy Efficiency and Thermal Management

The Dell 575TK’s 300W TDP design demonstrates a careful balance between performance and energy consumption. The passive cooling system allows integration in data centers with controlled airflow, ensuring that multiple GPUs can operate in parallel without overheating. Its thermal profile is optimized for 24/7 continuous workloads, making it suitable for mission-critical applications. Dell’s engineering ensures that the GPU’s components are robust enough to withstand heavy computational cycles, minimizing downtime and maintaining system integrity under full load.

Server Integration and Compatibility

This GPU is compatible with Dell PowerEdge server models such as the R750, R7525, R740, and other systems designed to accommodate double-width PCIe GPUs. The Dell 575TK fits seamlessly into these environments, supported by BIOS and firmware optimizations that enhance stability. Its full-height, double-width passive design aligns with standard enterprise server chassis layouts, allowing smooth integration into dense rack configurations. Moreover, its compatibility with major software ecosystems, including CUDA, cuDNN, and TensorRT, ensures broad applicability across AI, HPC, and professional visualization tasks.

Deep Learning Training Capabilities

For deep learning practitioners, training models such as transformer-based architectures and convolutional neural networks becomes exponentially faster with the Dell 575TK. The GPU supports mixed precision training, which dynamically adjusts floating-point operations to maximize throughput while maintaining numerical stability. This method dramatically reduces training time and increases energy efficiency. Developers using frameworks like PyTorch, TensorFlow, and JAX benefit from native optimization for the A100 architecture, achieving higher performance with minimal code modifications.

AI Inference Optimization

The A100 architecture features specialized Tensor Cores designed to handle inference workloads at unprecedented speed. The Dell 575TK leverages these cores to deploy AI models in real-time applications such as recommendation systems, fraud detection, speech processing, and natural language understanding. The inclusion of sparsity support allows the GPU to skip zero-value operations, enhancing inference speed and reducing power draw. This intelligent execution model ensures optimal performance for enterprise AI services requiring low-latency responses.

High-Performance Computing and Scientific Research

Beyond AI, the Dell 575TK GPU excels in high-performance computing applications. Its architecture supports FP64 double-precision performance required in scientific modeling, molecular dynamics, and physics simulations. The GPU’s enhanced compute density allows researchers to conduct complex simulations on fewer nodes, minimizing hardware costs and energy consumption. The Nvidia CUDA ecosystem ensures that scientific codes can be easily ported to the GPU, accelerating research across disciplines such as climatology, genomics, and quantum chemistry.

Parallel Computing Efficiency

With over 6,900 CUDA cores, the Ampere A100 within the Dell 575TK executes parallel tasks with remarkable efficiency. It supports advanced features such as asynchronous data transfers, multi-streaming, and concurrent kernel execution. These capabilities allow simultaneous computation and communication, effectively overlapping data movement with processing. As a result, researchers experience reduced idle time, higher throughput, and improved scaling across distributed systems. The integration with CUDA-aware MPI environments allows the GPU to perform efficiently in multi-node HPC clusters.

Energy-Conscious Performance in HPC Workflows

The Dell 575TK GPU’s 300W design ensures maximum computational performance without excessive power consumption. Its passive cooling approach leverages the data center’s airflow management systems, maintaining temperature efficiency even under prolonged high workloads. This makes it suitable for sustainable HPC infrastructures seeking to balance performance with energy efficiency. The combination of performance-per-watt and compute density makes this GPU a key component in modern energy-conscious data centers.

Enterprise Reliability and Scalability

Dell’s engineering emphasizes enterprise reliability, ensuring that the 575TK GPU integrates seamlessly with mission-critical environments. Each component undergoes extensive validation for thermal stability, performance consistency, and firmware compatibility. Dell’s end-to-end support ensures predictable deployment, whether the GPU is installed in on-premise data centers or integrated within hybrid cloud ecosystems. The scalability of the Nvidia A100 GPU allows enterprises to expand compute capacity incrementally, aligning with evolving workload demands.

Cloud Integration and Virtualization Support

The Dell 575TK GPU is fully compatible with Nvidia’s virtualization technologies, including vGPU and CUDA virtualization. This allows organizations to allocate GPU resources across virtual machines and containers efficiently. Cloud service providers can use the GPU to deliver AI and compute services to multiple tenants without compromising performance isolation. Integration with Kubernetes and Docker ensures that AI workloads can be deployed flexibly, supporting DevOps pipelines and continuous integration workflows.

Optimized Framework Compatibility

Deep learning frameworks like TensorFlow, PyTorch, and MXNet offer native optimizations for the Nvidia Ampere architecture. This ensures that the Dell 575TK GPU achieves peak utilization during training and inference. The inclusion of TensorRT enhances inference acceleration, while Nvidia’s Nsight suite provides debugging and profiling tools to optimize GPU performance. Developers can fine-tune kernel performance, monitor bottlenecks, and adjust code for maximum throughput.

Integration with Next-Generation Servers

As Dell continues to develop advanced PowerEdge systems, the 575TK GPU remains compatible with future generations of hardware. Its PCIe Gen4 interface ensures forward compatibility with upcoming server architectures supporting Gen5 and beyond. Organizations investing in this GPU benefit from extended lifecycle value, reduced total cost of ownership, and ongoing support from Dell’s enterprise infrastructure team.

Sustainability and Data Center Optimization

Energy-efficient computing is at the core of modern data center design. The Dell 575TK’s 300W power envelope aligns with sustainability goals by reducing power draw per performance unit. Its passive cooling design minimizes the need for active fan systems, lowering noise and energy consumption. Combined with Dell’s data center management tools, it enables predictive cooling, smart airflow management, and reduced carbon footprint.