- Graphic card benchmark upgrade#
- Graphic card benchmark pro#
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- Graphic card benchmark professional#
This isn’t always the case – the Quadro RTX 4000 has the same 8GB of memory as its consumer counterpart, the GeForce RTX 2070 – but since workstation cards are geared towards memory-hungry tasks like GPU rendering, the extra capacity makes sense, and goes some way towards justifying the extra cost.Īnother key distinction between workstation GPUs and their consumer counterparts is their drivers. For example, although they all use the TU102 processor, the Quadro RTX 8000 and RTX 6000 have 48GB and 24GB of graphics memory respectively, whereas the consumer Quadro RTX 2080 Ti has 11GB.
Graphic card benchmark professional#
Professional GPUs typically carry much more memory than consumer variants based on similar parts. One of the main differences between the workstation cards on test and their cheaper consumer counterparts is the amount of on-board memory they possess. OpenCL 3.0, the specifications for which were revealed in April, may change that, but it has a long way to go. OpenCL has the advantage that it is hardware-agnostic, but CUDA and OptiX are currently more widely supported in DCC applications. The two firms also differ in the APIs they support for GPU computing: while both AMD and Nvidia support the open standard OpenCL, Nvidia focuses on its own CUDA and OptiX APIs. It’s important to note that comparing core counts is a reasonable way to judge the probable relative performance of different Nvidia cards, but not to compare Nvidia cards with those from AMD, which have a different architecture, and group processing cores into ‘compute units’ instead.
Graphic card benchmark Offline#
Now that the Turing architecture is nearly two years old, we are starting to see widespread support for hardware-accelerated ray tracing in CG software, with offline renderers like Arnold, KeyShot, V-Ray and Blender’s Cycles engine accessing the RT cores via Nvidia’s OptiX API, and game engines like Unity and Unreal Engine doing so via DXR, DirectX 12’s ray tracing API. Nvidia’s current Turing GPU architecture features three types of processor cores: CUDA cores, designed for general GPU computing Tensor cores, designed for machine learning operations and RT cores, new in the Turing-based RTX cards, and designed for ray tracing calculations. If you’re already familiar with them, you may want to skip ahead. Technology focus: consumer vs workstation cardsīefore we discuss the cards on test, let’s run through a few of the technical terms that will recur throughout the course of this review. Technology focus: GPU architectures, memory types and APIs
Graphic card benchmark pro#
This time round, I will be putting the cards on test through the same benchmarks as in that February review, but looking at many of the professional workstation GPUs currently on the market, including Nvidia’s entire Quadro RTX line-up – the Quadro RTX 8000, 6000, 50 – and three of AMD’s Radeon Pro cards: the current-gen Radeon Pro W5700 and W5500, and the previous-gen Radeon Pro WX 8200.
Graphic card benchmark Pc#
Also, you can run our Free PC Benchmark to rate the performance of your own GPU and check its specs.Which workstation-class GPU is best for your DCC work? Jason Lewis puts Nvidia’s current Quadro RTX cards and three of AMD’s Radeon Pro GPUs through a battery of real-world benchmarks to find out.īack in February, I did a review of Nvidia’s GeForce RTX 2080 Ti, comparing it to several of the firm’s other high-end consumer GPUs: both its current cards and previous-gen cards still widely used in production.
Graphic card benchmark upgrade#
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