NVIDIA Tesla K40d
NVIDIA graphics card specifications and benchmark scores
At a Glance
NVIDIANVIDIA Tesla K40d Specifications
GPU Core
Shader units and compute resources
The NVIDIA Tesla K40d GPU core specifications define its raw processing power for graphics and compute workloads. Shading units (also called CUDA cores, stream processors, or execution units depending on manufacturer) handle the parallel calculations required for rendering. TMUs (Texture Mapping Units) process texture data, while ROPs (Render Output Units) handle final pixel output. Higher shader counts generally translate to better GPU benchmark performance, especially in demanding games and 3D applications.
Tesla K40d Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the Tesla K40d's performance in GPU benchmarks and real-world gaming. The base clock represents the minimum guaranteed frequency, while the boost clock indicates peak performance under optimal thermal conditions. Memory clock speed affects texture loading and frame buffer operations. The Tesla K40d by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
NVIDIA's Tesla K40d Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla K40d's memory capacity determines how well it handles high-resolution textures and multiple displays. Memory bandwidth, measured in GB/s, affects how quickly data moves between the GPU and VRAM. Higher bandwidth improves performance in memory-intensive scenarios like 4K gaming. The memory bus width and type (GDDR6, GDDR6X, HBM) significantly influence overall GPU benchmark scores.
Tesla K40d by NVIDIA Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the Tesla K40d, reducing the need to fetch data from slower VRAM. L1 and L2 caches store frequently accessed data close to the compute units. AMD's Infinity Cache (L3) dramatically increases effective bandwidth, improving GPU benchmark performance without requiring wider memory buses. Larger cache sizes help maintain high frame rates in memory-bound scenarios and reduce power consumption by minimizing VRAM accesses.
Tesla K40d Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla K40d against other graphics cards. FP32 (single-precision) performance, measured in TFLOPS, indicates compute capability for gaming and general GPU workloads. FP64 (double-precision) matters for scientific computing. Pixel and texture fill rates determine how quickly the GPU can render complex scenes. While real-world GPU benchmark results depend on many factors, these specifications help predict relative performance levels.
Kepler Architecture & Process
Manufacturing and design details
The NVIDIA Tesla K40d is built on NVIDIA's Kepler architecture, which defines how the GPU processes graphics and compute workloads. The manufacturing process node affects power efficiency, thermal characteristics, and maximum clock speeds. Smaller process nodes pack more transistors into the same die area, enabling higher performance per watt. Understanding the architecture helps predict how the Tesla K40d will perform in GPU benchmarks compared to previous generations.
Power & Thermal
TDP and power requirements
Power specifications for the NVIDIA Tesla K40d determine PSU requirements and thermal management needs. TDP (Thermal Design Power) indicates the heat output under typical loads, guiding cooler selection. Power connector requirements ensure adequate power delivery for stable operation during demanding GPU benchmarks. The suggested PSU wattage accounts for the entire system, not just the graphics card. Efficient power delivery enables the Tesla K40d to maintain boost clocks without throttling.
Tesla K40d by NVIDIA Physical & Connectivity
Dimensions and outputs
Physical dimensions of the NVIDIA Tesla K40d are critical for case compatibility. Card length, height, and slot width determine whether it fits in your chassis. The PCIe interface version affects bandwidth for communication with the CPU. Display outputs define monitor connectivity options, with modern cards supporting multiple high-resolution displays simultaneously. Verify these specifications against your case and motherboard before purchasing to ensure a proper fit.
NVIDIA API Support
Graphics and compute APIs
API support determines which games and applications can fully utilize the NVIDIA Tesla K40d. DirectX 12 Ultimate enables advanced features like ray tracing and variable rate shading. Vulkan provides cross-platform graphics capabilities with low-level hardware access. OpenGL remains important for professional applications and older games. CUDA (NVIDIA) and OpenCL enable GPU compute for video editing, 3D rendering, and scientific applications. Higher API versions unlock newer graphical features in GPU benchmarks and games.
Tesla K40d Product Information
Release and pricing details
The NVIDIA Tesla K40d is manufactured by NVIDIA as part of their graphics card lineup. Release date and launch pricing provide context for comparing GPU benchmark results with competing products from the same era. Understanding the product lifecycle helps evaluate whether the Tesla K40d by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
About NVIDIA Tesla K40d
The NVIDIA Tesla K40d is a compute-oriented accelerator built on the Kepler architecture, using the GK110B chip manufactured on TSMC's 28 nm process. It packs 7,080 million transistors on a 561 mm² die, with a transistor density of 12.6M per mm². The card carries 12 GB of GDDR5 memory on a 384-bit bus, delivering 288.4 GB/s of bandwidth. Its base clock runs at 745 MHz with a boost of 876 MHz, while memory operates at 1502 MHz (6 Gbps effective). The K40d provides 2880 shading units, 240 texture mapping units, and 48 ROPs, with peak rates of 52.56 GPixel/s pixel fill, 210.2 GTexel/s texture fill, and 5.046 TFLOPS FP32 compute. It is a dual-slot card, 267 mm (10.5 inches) long, with no display outputs, and is positioned at the 50th percentile of all GPUs in the database. Released on 2013-11-21, it sits between the Tesla Fermi and Tesla Maxwell generations, and its production status is end-of-life.
Power and Cooling
The Tesla K40d has a thermal design power (TDP) of 245 W, which is a moderate figure for a dual-slot accelerator of its era. The suggested power supply unit (PSU) rating is 550 W, indicating that a system with a 550 W PSU is considered sufficient to power the card along with typical accompanying components. The dual-slot form factor implies a substantial cooling solution, likely a blower-style heatsink that exhausts air out of the chassis, which is common for compute cards that may be densely packed in servers. The card's length of 267 mm (10.5 inches) is a standard size for dual-slot GPUs, and it fits into most full-sized server or workstation cases. Notably, the FACT PACK does not list specific power connector requirements, so the exact number of 8-pin or 6-pin connectors is not documented here. The absence of display outputs means that the card does not require any video output connectors, simplifying its power delivery design. The 245 W TDP is consistent with the performance tier implied by the 50th percentile ranking, and the 550 W PSU recommendation provides a comfortable margin for systems with a single such card. For multi-GPU configurations, users would need to scale the PSU capacity accordingly, but that calculation is beyond the data provided.
Who Should Consider It
The Tesla K40d is not a consumer graphics card; it has no display outputs, so it cannot drive a monitor directly. Its intended role is compute acceleration in servers, workstations, or clusters. The 12 GB GDDR5 memory and 288.4 GB/s bandwidth are well-suited for data-intensive workloads that require large working sets, such as scientific simulations, financial modeling, or rendering tasks that fit within the 12 GB frame buffer. The FP32 compute rate of 5.046 TFLOPS provides a theoretical ceiling for single-precision floating-point operations, which is relevant for many general-purpose compute workloads. However, because the FACT PACK contains no benchmark scores, it is not possible to give specific resolution-based or settings-based recommendations for gaming or real-time graphics. The card's 50th percentile position among all GPUs suggests that, within the database's population, it performs at an average level relative to every other GPU tracked. This percentile is a relative measure, but without absolute scores, it cannot be translated into concrete frame rates or compute times. Therefore, the K40d is best considered by users who need a large memory pool and moderate compute throughput for non-graphical tasks, and who are comfortable with a card that offers no video output. For workloads that require high FP32 throughput and ample VRAM, the K40d's specifications are adequate, but the lack of benchmark data means that real-world performance must be evaluated through independent testing.
Ray Tracing and Feature Set
The Tesla K40d does not include dedicated ray tracing cores or tensor cores; the FACT PACK lists these as null. This means the card relies entirely on the traditional Kepler shader architecture for all rendering and compute tasks. It does not have hardware acceleration for real-time ray tracing or AI-based features such as deep learning super sampling. The API support includes DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.175. The DirectX 12 entry of "12 (11_1)" indicates that the card supports DirectX 12 at feature level 11_1, which is a subset of the full DirectX 12 feature set. This is typical for Kepler-generation hardware, which predates the full DirectX 12 Ultimate specification. OpenGL 4.6 and Vulkan 1.2.175 are relatively recent API versions, suggesting that the driver stack for this card has been maintained to support modern compute and graphics interfaces, even though the hardware is older. The absence of tensor cores means that any machine learning workloads would have to rely on traditional shader-based compute, which is less efficient than dedicated tensor hardware. Similarly, without RT cores, any ray tracing would be performed in software on the shader units, which is not practical for real-time use. The card's feature set is thus limited to conventional rasterization and compute, with no specialized acceleration blocks.
How It Compares
The FACT PACK does not provide any nearest rival data for the Tesla K40d, so a direct comparison to specific competitor cards is not possible from the given information. The card's position in the product stack is defined by its generation: it is part of the Tesla Kepler family, succeeding the Tesla Fermi line and preceding the Tesla Maxwell line. This chronological placement indicates that the K40d represents a step forward in architecture and efficiency relative to Fermi, but it is superseded by Maxwell in terms of performance-per-watt and possibly raw throughput. The 50th percentile ranking among all GPUs in the database gives a broad sense of its standing: it is exactly in the middle of the distribution, meaning half of all tracked GPUs are faster and half are slower. This percentile is a composite measure, but without benchmark scores or a list of rivals, it cannot be broken down further. The lack of recorded benchmarks (the benchmarks array is empty) means that no average score or performance delta can be cited. In the absence of rival data, the K40d's own specifications serve as the only basis for evaluation. Its 12 GB memory and 288.4 GB/s bandwidth are generous for its era, but its FP32 throughput of 5.046 TFLOPS is modest by modern standards. The card's dual-slot design and 245 W TDP are typical for compute accelerators of its time.
Benchmark Performance
The Tesla K40d has no recorded benchmark scores in the FACT PACK, so there are no absolute performance numbers to analyze. The only performance-related figure is the percentile rank of 50, which places it at the median of all GPUs in the database. This percentile is a relative indicator, but without a distribution of scores, it does not convey how much faster or slower the card is compared to other entries. The theoretical peak rates, however, provide a sense of its computational capability. The FP32 performance of 5.046 TFLOPS is the maximum single-precision throughput the hardware can achieve under ideal conditions. The texture rate of 210.2 GTexel/s and pixel rate of 52.56 GPixel/s are similarly theoretical maxima for texture and pixel processing. These numbers are derived from the core clock and the number of functional units: 2880 shading units, 240 TMUs, and 48 ROPs. The memory bandwidth of 288.4 GB/s, based on a 384-bit bus and 6 Gbps effective GDDR5, is a key factor for memory-bound workloads. In practice, real-world performance would be lower than these theoretical peaks due to inefficiencies, driver overhead, and workload characteristics. Because no benchmark scores are provided, it is not possible to state, for example, that the card is 30% ahead of a rival in multi-core performance. The percentile of 50 is the sole quantitative performance comparison available, and it suggests that the K40d is an average performer among all GPUs tracked by this database. Users seeking specific performance numbers for applications such as rendering, simulation, or machine learning would need to consult independent benchmarks or run their own tests.
FAQ
Q: What is the thermal design power (TDP) of the Tesla K40d?
A: The TDP is 245 W.
Q: What power supply unit rating is recommended for the Tesla K40d?
A: The suggested PSU is 550 W.
Q: Does the Tesla K40d have any display outputs?
A: No, the card has no display outputs.
Q: How much memory does the Tesla K40d have and what type is it?
A: It has 12 GB of GDDR5 memory on a 384-bit bus, with a bandwidth of 288.4 GB/s.
Q: Which graphics APIs does the Tesla K40d support?
A: It supports DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.175.
Q: What was the launch MSRP of the Tesla K40d?
A: The launch MSRP was 7,699 USD.
Detailed benchmark scores and charts for the NVIDIA Tesla K40d are below.
Benchmark Scores
No benchmark data available for this GPU.
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