Examples of using Gpu-accelerated in English and their translations into Chinese
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In situations where data movement can be a bottleneck, the Kinetica platform uses native TensorFlow integration to bring GPU-accelerated workloads directly to large data sets.
By working closely with NVIDIA and harnessing the power of GPU-accelerated systems, we have made Cognitive Toolkit and Microsoft Azure the fastest, most versatile AI platform.
Keep everyone in sync with Team Projects, work with extruded 3D text and shapes right in the timeline, and render faster with more GPU-accelerated effects.
The GPU-Accelerated Spatial Database.
Adobe recommended graphics card for GPU-accelerated playback.
GPU-accelerated RED RAW processing with support for dual GPUs.
Record number of GPU-accelerated systems join TOP500 list.
Conversational AI is a major driver for GPU-accelerated inference.
TeraChem is the first fully GPU-accelerated quantum chemistry software.
For GPU system requirements, see Considerations for GPU-accelerated features.
CUDA platform provides a comprehensive development environment for C and C++ developers building GPU-accelerated applications.
Due to the great potential of the developed technology, this GPU-accelerated software was subsequently commercialized.
NVIDIA will also provide technical and business advice to members regarding its GPU-accelerated products and services.
High-performance computing, virtualization and web service providers have created demand for our GPU-accelerated data centre platforms.
The Video Limiter feature is a GPU-accelerated effect that limits the video signals to broadcast-legal range.
The function of this framework is to make it easy to exploit GPU-accelerated video encode/decode from Python.
To help more researchers experience the power of GPU-accelerated research, NVIDIA has launched the GPU Test Drive program.
The NVIDIA Deep Learning SDK provides powerful tools and libraries for designing and deploying GPU-accelerated deep learning applications including logistic regression.
NVIDIA Image Compute Engine- GPU-accelerated service with REST API that image resizing 5 times faster compared to a CPU.
By training its GPU-accelerated deep learning software to recognize ultrasound images, it aims to make scans easier to interpret.