To illustrate the operation of the design platform, two well-known deep CNNs are used, which are YOLOv3 and faster RCNN. This technology can be used to explore and to optimize the hardware architectures of the CNNs so that the cost can be minimized....
Chips&Media refined this algorithmic C model into synthesizable C code and used the Catapult HLS Platform to rapidly explore various architectures and synthesize into RTL to find the optimal solution for this type of design. “In multiple application spaces where the market is rapidly ch...
GPU Coder Interface for Deep Learning integrates with the following deep learning accelerator libraries and the corresponding GPU architectures: cuDNN and TensorRT libraries for NVIDIA GPUs ARM Compute Library for ARM Mali GPUs Platform and Release Support ...
Our family of Neural Decision Processors (NDPs) are specifically designed to run deep learning models, providing 100x the efficiency and 10/30x the throughput of existing low-power MCUs. From acoustic event detection for security applications to video processing in teleconferencing, our hardware can...
In some cases, it may be useful to generate benchmarking executables for multiple architectures. For example, some systems may have multiple graphics processors with different architectures installed. The NVIDIA compiler (nvcc) supports the generation of "fat binaries" that contain intermediate and comp...
Deep learning architectures (DLA) have shown impressive performance in computer vision, natural language processing and so on. Many DLA make use of cloud computing to achieve classification due to the high computation and memory requirements. Privacy and latency concerns resulting from cloud computing ...
Supported Hardware Support for third-party hardware such as Inteland XilinxFPGA boards Deep Learning HDL Toolbox™ supports the hardware listed in this table. How to Get Best Site Performance Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites ...
MOB LEC2 Hardware and Software Architectures Synchronized Hardware To synchronize different modules / sensors on a robot to provide a common clock...Computing hardware Making decision Takes in all sensory data and computes actions for the robot...Service robots have low requirements for the computing...
Machine learning has become ubiquitous in modern data analysis, decision-making, and optimization. A prominent subset of machine learning is the artificial deep neural network (DNN), which has revolutionized many fields, including classification1, translation2and prediction3,4. An important step toward...
You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-...