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  2. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    Devices that support compute capability 2.0 and above support denormal numbers, and the division and square root operations are IEEE 754 compliant by default. However, users can obtain the prior faster gaming-grade math of compute capability 1.x devices if desired by setting compiler flags to disable accurate divisions and accurate square roots ...

  3. Maxwell (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Maxwell_(microarchitecture)

    Photo of James Clerk Maxwell, eponym of architecture. Maxwell is the codename for a GPU microarchitecture developed by Nvidia as the successor to the Kepler microarchitecture. . The Maxwell architecture was introduced in later models of the GeForce 700 series and is also used in the GeForce 800M series, GeForce 900 series, and Quadro Mxxx series, as well as some Jetson produ

  4. List of Nvidia graphics processing units - Wikipedia

    en.wikipedia.org/wiki/List_of_Nvidia_graphics...

    Compute Capability: 1.1 (G92 [GTS250] GPU) Compute Capability: 1.2 (GT215, GT216, GT218 GPUs) Compute Capability: 1.3 has double precision support for use in GPGPU applications.

  5. Volta (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Volta_(microarchitecture)

    Volta is the codename, but not the trademark, [1] for a GPU microarchitecture developed by Nvidia, succeeding Pascal. It was first announced on a roadmap in March 2013, [2] although the first product was not announced until May 2017. [3] The architecture is named after 18th–19th century Italian chemist and physicist Alessandro Volta.

  6. Graphics Core Next - Wikipedia

    en.wikipedia.org/wiki/Graphics_Core_Next

    As of July 2017, the Graphics Core Next instruction set has seen five iterations. The differences between the first four generations are rather minimal, but the fifth-generation GCN architecture features heavily modified stream processors to improve performance and support the simultaneous processing of two lower-precision numbers in place of a single higher-precision number.

  7. General-purpose computing on graphics processing units

    en.wikipedia.org/wiki/General-purpose_computing...

    3–4x: T 2075, 2090, K10, K20, K20X: Single only: Available now, version 2.2.26 GPU-HMMER: Parallelized local and global search with profile hidden Markov models: Parallel local and global search of hidden Markov models: 60–100x: T 2075, 2090, K10, K20, K20X: Yes: Available now, version 2.3.2 mCUDA-MEME: Ultrafast scalable motif discovery ...

  8. Template:Nvidia Tesla - Wikipedia

    en.wikipedia.org/wiki/Template:Nvidia_Tesla

    C2050 GPU Computing Module [4] Fermi: July 25, 2011 1× GF100 575 448 1,150 — GDDR5 384 3 [g] 3000 144 No 1.0304 0.5152 2.0 247 Internal PCIe GPU (full-height, dual-slot) M2050 GPU Computing Module [5] July 25, 2011 — 3,092 148.4 No 225 C2070 GPU Computing Module [4] July 25, 2011 1× GF100 575 448 1,150 — GDDR5 384 6 [g] 3,000 144 No 1. ...

  9. Ampere (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Ampere_(microarchitecture)

    CUDA Compute Capability 8.0 for A100 and 8.6 for the GeForce 30 series [7] TSMC's 7 nm FinFET process for A100; Custom version of Samsung's 8 nm process (8N) for the GeForce 30 series [8] Third-generation Tensor Cores with FP16, bfloat16, TensorFloat-32 (TF32) and FP64 support and sparsity acceleration. [9]