Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
Turing is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia. It is named after the prominent mathematician and computer scientist Alan Turing. The architecture was first introduced in August 2018 at SIGGRAPH 2018 in the workstation-oriented Quadro RTX cards, and one week later at Gamescom in consumer GeForce 20…
The analysis highlights Measurement and Products as prominent areas in the source structure around Turing (microarchitecture).
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Turing (microarchitecture) shows recurring relationship patterns in the source. For example, Turing (microarchitecture) → DisplayPort 1.4a, HDMI 2.0b, USB-C Another extracted example is Turing (microarchitecture) → 10-bit, 8-bit. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
turing cores nvidia tensor rtx ray tracing ray-tracing using series architecture rt graphics geforce process vulkan volta gpu quadro 20
TTTA extracted 36 structured relationships around Turing (microarchitecture). Examples in this analysis include Turing (microarchitecture) → Codenames → TU10x TU11x and Turing (microarchitecture) → Color bit-depth → 8-bit. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Turing (microarchitecture) | Codenames | TU10x TU11x | 1.00 | infobox |
| Turing (microarchitecture) | Color bit-depth | 8-bit | 1.00 | infobox |
| Turing (microarchitecture) | Color bit-depth | 10-bit | 1.00 | infobox |
| Turing (microarchitecture) | Compute | 28.5 TFLOPS (FP16) | 1.00 | infobox |
| Turing (microarchitecture) | Compute | 14.2 TFLOPS (FP32) | 1.00 | infobox |
| Turing (microarchitecture) | CUDA | Compute Capability 7.5 | 1.00 | infobox |
| Turing (microarchitecture) | Decode codecs | H.264 | 1.00 | infobox |
| Turing (microarchitecture) | Decode codecs | H.265 | 1.00 | infobox |
| Turing (microarchitecture) | Designed by | Nvidia | 1.00 | infobox |
| Turing (microarchitecture) | Desktop | GeForce GTX 16 series GeForce RTX 20 series | 1.00 | infobox |
| Turing (microarchitecture) | Direct3D | Direct3D 12.0 | 1.00 | infobox |
| Turing (microarchitecture) | DirectX | DirectX 12 Ultimate (Feature Level 12_2) | 1.00 | infobox |
| Turing (microarchitecture) | Display outputs | DisplayPort 1.4a | 1.00 | infobox |
| Turing (microarchitecture) | Display outputs | HDMI 2.0b | 1.00 | infobox |
| Turing (microarchitecture) | Display outputs | USB-C | 1.00 | infobox |
| Turing (microarchitecture) | Encode codecs | H.264 | 1.00 | infobox |
| Turing (microarchitecture) | Encode codecs | H.265 | 1.00 | infobox |
| Turing (microarchitecture) | Encoder supported | NVENC | 1.00 | infobox |
| Turing (microarchitecture) | Fabrication process | TSMC 12FFC | 1.00 | infobox |
| Turing (microarchitecture) | L1 cache | 96 KB (per SM) | 1.00 | infobox |
| Turing (microarchitecture) | L2 cache | 2 MB to 6 MB | 1.00 | infobox |
| Turing (microarchitecture) | Launched | September 20, 2018; 7 years ago (2018-09-20) | 1.00 | infobox |
| Turing (microarchitecture) | Manufactured by | TSMC | 1.00 | infobox |
| Turing (microarchitecture) | Memory support | GDDR6 GDDR5 HBM2 | 1.00 | infobox |
| Turing (microarchitecture) | OpenCL | OpenCL 3.0 | 1.00 | infobox |
| Turing (microarchitecture) | OpenGL | OpenGL 4.6 | 1.00 | infobox |
| Turing (microarchitecture) | PCIe support | PCIe 3.0 | 1.00 | infobox |
| Turing (microarchitecture) | Predecessor | Pascal | 1.00 | infobox |
| Turing (microarchitecture) | Professional/workstation | Quadro RTX | 1.00 | infobox |
| Turing (microarchitecture) | Server/datacenter | Tesla T4 | 1.00 | infobox |
The concept neighborhoods around Turing (microarchitecture) bring nearby vocabulary together. In this analysis, examples include Nvidia, Geforce and Quadro. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Turing (microarchitecture), one of the stronger structural bridges in this analysis connects Turing (microarchitecture) with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Turing (microarchitecture) to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Measurement & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Turing (microarchitecture) · EN edition · Analysis: TopicsToTalkAbout