Targeted at modern data center workloads, NVIDIA’s L40S is engineered to redefine graphics and media acceleration. This GPU is specifically crafted to meet the growing demands of graphics-intensive and media-heavy applications in data centers. Its robust performance in delivering high-quality graphics...
Just six months later, NVIDIA announced its first DPU, a data processor that defines a new level of security, storage and network acceleration. A roadmap of BlueField DPUs is already gaining traction in supercomputers, cloud services, OEM systems and third-party software. By June 2021, 342 of...
Elastic GPU Service,Elastic GPU Service:Elastic GPU Service provides GPU-accelerated computing capabilities and ready-to-use and scalable GPU computing resources. Elastic GPU Service is an elastic computing service provided by Alibaba Cloud...
Acceleration of Model Training: GPU servers efficiently handle concurrent calculations to train deep learning models faster. This acceleration allows data scientists and machine learning engineers to experiment faster. Handling Large Datasets: GPUs can parallelly analyze enormous datasets, making them perfect...
The lack of CUDA cores here is generally offset by the better computing resources for single-threaded tasks. Maximizing Computing Resources With a GPU Dedicated Server The explosion of AI acceleration through CUDA cores and GPU hosting has made a significant impact on the world. Beyond just block...
Windows 365 will support Hardware High Efficiency Video Coding (HEVC) h.265 4:2:0 on Compatible GPU-enabled Cloud PCs. For more information, see Enable GPU acceleration for Azure Virtual Desktop. Windows App Windows App is now generally available Windows App has moved out of preview and into...
GPU for Machine Learning Some of the most exciting applications for GPU technology involve AI and machine learning. Because GPUs incorporate an extraordinary amount of computational capability, they can deliver incredible acceleration in workloads that take advantage of the highly parallel nature of GPUs...
Reduced E2E latency and some performance issues by optimizing the GPU render path in the Windows Desktop client. To enable the new render path, add the registry keyHKEY_CURRENT_USER \SOFTWARE\Microsoft\Terminal Server Client\IsSwapChainRenderingEnabledand set its value to00000001. To disa...
1:53 Video length is 1:53 Description Full Transcript Related Resources What Is GPU Coder? GPU Coder™ generates optimized CUDA® code from MATLAB® code and Simulink® models. The generated code includes CUDA kernels for parallelizable parts of your deep learning, embedded vision, and si...
Learn about the CPU vs GPU difference, explore uses and the architecture benefits, and their roles for accelerating deep-learning and AI.