NVIDIA Tesla V100 SXM2 32 GB

The NVIDIA Tesla V100 SXM2 32 GB is a Volta-architecture compute module built around the GV100 chip. TSMC fabricates it on a 12 nm process, with 21,100 million transistors in an 815 mm² die and a transistor density of 25.9M per mm². The database lists it as End-of-life, with a release date of 2018-03-26. It belongs to the Tesla Volta (Vxx) generation, sitting between Tesla Pascal as predecessor and Tesla Turing as successor.

Memory Subsystem

The memory system is the strongest single feature in the database entry. The V100 SXM2 32 GB uses 32 GB of HBM2, and that memory is attached through a 4096-bit bus. The peak bandwidth is listed as 898.0 GB/s, which is the figure that matters when a workload must constantly move large amounts of data. The memory clock is 877 MHz, with an effective data rate of 1754 Mbps, and that effective rate is exactly double the memory clock. The 4096-bit bus is what turns that effective data rate into 898.0 GB/s of bandwidth.

For high-resolution workloads, capacity and bandwidth perform different roles. The 32 GB pool can hold large framebuffers, textures, or datasets on the module itself. When a working set fits in HBM2, the system does not need to stream the same data repeatedly over the host interface. When data must move, the local memory path is 898.0 GB/s, while the host connection is PCIe 3.0 x16. The gap between those two paths affects the kind of workload this module can handle: large resident buffers and high-bandwidth access. A memory-bound kernel would be constrained by the speed at which data can be fed through the 4096-bit bus, not by a narrow memory path. The combination of 32 GB capacity and 898.0 GB/s bandwidth gives this GPU a memory subsystem built for both size and throughput.

Ray Tracing and Feature Set

The database entry does not quantify ray tracing hardware. The rtCores field is null, so there is no ray tracing core count to report from the data. What the data does quantify are 640 tensor cores. Those tensor cores sit alongside a compute layout of 5120 shading units, 320 TMUs, and 128 ROPs. The listed pixel rate is 195.8 GPixel/s, and the listed texture rate is 489.6 GTexel/s. Those rates are peak specification numbers, driven by the 128 ROPs and 320 TMUs at the boost clock.

API support in the data is DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The DirectX entry is recorded as a feature level, not as a ray tracing feature set. The module also has No display outputs, so these APIs apply to compute or off-screen rendering rather than to driving a monitor directly. The feature set is therefore not a display-oriented feature set. It is a compute-oriented set in which the 640 tensor cores and the FP16 throughput are the most distinctive items. The FP16 figure is listed as 31.33 TFLOPS at a 2:1 ratio against FP32, which makes mixed-precision work an obvious fit. Without an RT core count, any ray tracing capability cannot be established from this database entry.

Benchmark Performance

The benchmarks array is empty, and the avgBenchmarkScore field is 0. There are no sampled results to analyze. The percentileVsAllGpus field is 50, which places this GPU at the midpoint of the database's GPU list, but that percentile is not supported by a nonzero benchmark score. It is a database rank, not a measured performance result.

The quantitative identity of the V100 SXM2 32 GB therefore comes from its specification sheet. The base clock is 1290 MHz, the boost clock is 1530 MHz, and the peak FP32 rate is 15.67 TFLOPS. The peak FP16 rate is 31.33 TFLOPS, exactly double the FP32 rate, matching the 2:1 ratio recorded in the data. The pixel rate is 195.8 GPixel/s, and the texture rate is 489.6 GTexel/s. These are peak throughput figures, not application averages. Without benchmark scores, no deltaPct values can be calculated from rivals, and no relative performance statements can be made from that side of the data. The 50th percentile is the only all-GPU placement in the database, and it should be understood in the context of a missing benchmark average.

Who Should Consider It

This is not a conventional desktop graphics card. The slot width is SXM Module, the display outputs are listed as No outputs, and the power connectors are listed as None. A system using this module should still account for a 250 W TDP and a suggested PSU of 600 W, because power is delivered through the host platform rather than through on-board connectors. The intended environment is a server or compute node that can integrate an SXM module. A user who needs a display connection cannot get one from this device.

For high-resolution workloads, the relevant reasons to consider this SKU are the 32 GB HBM2 pool and the 898.0 GB/s bandwidth. Those two numbers allow large resident allocations and fast local transfers. The 640 tensor cores and 31.33 TFLOPS FP16 rate make tensor-heavy workloads a natural match. The 15.67 TFLOPS FP32 rate is also substantial for general compute. The API set, including DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4, gives software compatibility across several compute and rendering paths. Without benchmark scores, the data cannot support a settings-based or frame-rate-based recommendation. The decision should instead be driven by memory capacity, memory bandwidth, tensor throughput, and the absence of display outputs. If the workload is a high-resolution dataset that fits in 32 GB and requires high-bandwidth access, this module's specification sheet is aligned with that use. If the workload expects a standard graphics card with display outputs and on-board power connectors, the data says this is not the right device.

How It Compares

The nearestRivals array is empty in the database, so there are no rival names, scores, or deltaPct values to report. That leaves this entry without a direct head-to-head comparison. The generation context is still present: Tesla Pascal is the predecessor, Tesla Turing is the successor, and this module belongs to the Tesla Volta (Vxx) line. The production status is End-of-life, and the release date is 2018-03-26. The only database rank is percentileVsAllGpus at 50, which is a midpoint placement against the full GPU list rather than a comparative result against a specific rival. Because no nearest rivals are supplied, no relative performance conclusion can be formed from the database's own comparison fields. The available positional statements are about generation, status, and aggregate percentile, not about performance relative to named competitors.