NVIDIA Tesla V100 PCIe 32 GB

The NVIDIA Tesla V100 PCIe 32 GB is a dual-slot, compute-focused accelerator built on the 12 nm Volta architecture, featuring the GV100 chip with 21,100 million transistors on an 815 mm² die. It targets server and workstation workloads, with a 50th percentile ranking among all GPUs in the database and no recorded average benchmark score, positioning it as a specialized compute part rather than a general gaming card.

How It Compares

The benchmark database lists no nearest rivals for this GPU, meaning its competitive positioning is derived solely from its architectural profile and absolute specifications. In the absence of direct score-based comparisons, the data shows a device engineered for high-throughput parallel processing, not for rasterization or real-time rendering. Its 50th percentile standing reflects a wide performance spread across all GPUs, but this metric is skewed by the absence of consumer-oriented benchmarks.

Without rival data, the analysis relies on internal consistency. The GPU’s FP32 throughput of 14.13 TFLOPS and FP16 of 28.26 TFLOPS (2:1 ratio) indicate a balanced design for mixed-precision workloads. The 640 tensor cores provide a distinct advantage for AI inference and training, a feature that would position it ahead of any non-tensor-core GPU in such tasks, though no specific rival percentages are available to quantify this.

The lack of display outputs confirms a non-visual compute role. Compared to a hypothetical gaming GPU, the absence of RT cores and display hardware would make it less suitable for interactive use, but the data does not provide direct rival scores to contrast. Consequently, the V100’s standing is best understood through its raw compute and memory resources rather than head-to-head deltas.

Ray Tracing and Feature Set

The Tesla V100 PCIe 32 GB does not include any ray tracing cores, as the `rtCores` field is null. This omission is consistent with its Volta architecture, which predates the Turing generation’s dedicated RT hardware. API support includes DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4, enabling modern compute and graphics APIs, but without hardware-accelerated ray tracing, any ray-traced workload would rely on software or compute shaders.

The feature set is anchored by 640 tensor cores, which accelerate matrix math for deep learning. These cores operate alongside 5120 shading units, 320 texture mapping units, and 128 raster output units, providing a robust foundation for general compute. The pixel rate of 176.6 GPixel/s and texture rate of 441.6 GTexel/s indicate strong fill rates for a compute card, though these metrics are secondary to the tensor core capabilities.

Volta’s architecture introduces independent thread scheduling and a unified memory architecture, though the fact pack does not detail these specifics. The API support for Vulkan 1.4 and DirectX 12 (12_1) ensures compatibility with modern compute frameworks, while the absence of display outputs eliminates any consumer graphics functionality. This is a pure accelerator, with its feature set optimized for data center tasks.

Memory Subsystem

The memory subsystem is a defining characteristic, featuring 32 GB of HBM2 on a 4096-bit bus, delivering 897.0 GB/s of bandwidth. This configuration is exceptionally wide, allowing for massive parallel data access. The effective memory clock is 1752 Mbps, which, combined with the bus width, yields the stated bandwidth figure.

For high-resolution workloads, the 32 GB capacity is substantial, accommodating large datasets, deep learning models, or high-resolution render targets without swapping. The 897.0 GB/s bandwidth ensures that the shading units and tensor cores are not starved for data, a critical factor for compute-intensive tasks. The 4096-bit bus is among the widest in the database, though no rival comparisons are provided to contextualize this.

The HBM2 type offers lower power consumption per byte compared to GDDR, though the fact pack does not specify comparative efficiency. For multi-GPU or cluster deployments, the memory capacity and bandwidth enable scaling of large-scale problems. The absence of a smaller VRAM variant in this pack means the 32 GB is the sole configuration, reinforcing its enterprise positioning.

FAQ

Q: What is the transistor count and die size of the Tesla V100 PCIe 32 GB?

A: It has 21,100 million transistors on an 815 mm² die, fabricated on a 12 nm process by TSMC.

Q: Does this GPU support hardware ray tracing?

A: No, the `rtCores` field is null, indicating no dedicated ray tracing cores. It relies on compute shaders for any ray tracing workloads.

Q: What are the memory specifications?

A: It has 32 GB of HBM2 with a 4096-bit bus width and 897.0 GB/s of bandwidth, with an effective memory clock of 1752 Mbps.

Q: What is the power consumption and PSU requirement?

A: The TDP is 250 W, with a suggested PSU of 600 W. It requires two 8-pin power connectors.

Q: What is the FP32 and FP16 performance?

A: FP32 performance is 14.13 TFLOPS, while FP16 is 28.26 TFLOPS with a 2:1 ratio.

Q: What is the production status and release date?

A: It is end-of-life, released on March 26, 2018, succeeding Tesla Pascal and preceding Tesla Turing.

Benchmark Performance

The benchmark data for the Tesla V100 PCIe 32 GB is sparse: the `benchmarks` array is empty, the `avgBenchmarkScore` is 0, and there are no nearest rivals with scores or deltaPct values. This absence of numerical comparisons prevents any direct percentage-based analysis against other GPUs. The only performance metric is the 50th percentile ranking among all GPUs, which indicates a median standing in a mixed database of consumer and professional parts.

Without rival scores, the analysis must pivot to theoretical throughput. The FP32 rate of 14.13 TFLOPS and FP16 rate of 28.26 TFLOPS provide a baseline for compute potential. The pixel rate of 176.6 GPixel/s and texture rate of 441.6 GTexel/s offer fill-rate figures, but these are not benchmark results. The 640 tensor cores are a unique asset, though their performance is not quantified in TFLOPS within the pack.

The 50th percentile suggests that in a database including gaming GPUs, this compute card lands in the middle, likely due to its lack of display outputs and gaming-oriented features. However, for its intended compute role, the absence of benchmark scores means no definitive performance ranking can be established. The data indicates a device that excels in raw compute but cannot be compared numerically to rivals due to missing data.

Power and Cooling

The Tesla V100 PCIe 32 GB has a TDP of 250 W, requiring a suggested PSU of 600 W. It uses two 8-pin power connectors, which is typical for a dual-slot card of this power class. The dual-slot width implies an active cooling solution, though the fact pack does not specify the cooler type or dimensions.

The 12 nm process node from TSMC contributes to the 250 W power envelope, balancing the 21,100 million transistors and high clock speeds (1230 MHz base, 1380 MHz boost). The memory clock of 876 MHz (1752 Mbps effective) adds to power draw, but the HBM2 type is generally efficient. The lack of display outputs reduces power consumption compared to a card with multiple display controllers.

For system integration, the 600 W PSU recommendation ensures sufficient headroom for the card and associated components. The 2x 8-pin connector requirement is standard for 250 W cards, providing stable power delivery. The dual-slot design suggests a robust heatsink and fan assembly, capable of dissipating the thermal load, though specific cooling performance is not quantified. The end-of-life status implies replacement by newer Tesla Turing parts, but power and cooling requirements remain relevant for existing deployments.