A ML-based resource utilization OpenCL GPU-kernel fusion model - ScienceDirect
HPVM: Hardware-Agnostic Programming for Heterogeneous Parallel Systems
Implementing OpenCL backend for pytorch - hardware-backends - PyTorch Dev Discussions
My GAN deep neural network that is learning how to write handwritten digits, running on AMD
The CNN2Gate overall architecture comprising a front-end parser (Open... | Download Scientific Diagram
Accelerating NNEF Framework on OpenCL Devices Using clDNN | Semantic Scholar
Applied Sciences | Free Full-Text | CitiusSynapse: A Deep Learning Framework for Embedded Systems
Accelerate your machine learning networks using TVM and the Adreno OpenCL ML APIs on Adreno GPUs - Qualcomm Developer Network
Low GPU usage by Keras / Tensorflow? - Stack Overflow
Hardware for Deep Learning. Part 3: GPU | by Grigory Sapunov | Intento
APIs for Accelerating Vision and Inferencing: An Overview of Options and Trade-offs
Nvidia - Part 3: Beyond GPUs, Software Moat, and Competition
Accelerating Convolutional Neural Networks in FPGA-based SoCs using a Soft-Core GPU | SpringerLink
Inference Engine, pytorch, opencl, keras, inference, tensorflow, Statistical classification, fieldprogrammable Gate Array, Deep learning, Coffee | Anyrgb
python - Keras Machine Learning Code are not using GPU - Stack Overflow
Evaluating PlaidML and GPU Support for Deep Learning on a Windows 10 Notebook | by franky | DataDrivenInvestor
OpenCL vs CUDA Comparisons | ArrayFire
Deep Learning Frameworks
Accelerate your machine learning networks using TVM and the Adreno OpenCL ML APIs on Adreno GPUs - Qualcomm Developer Network
Keras: Deep Learning Library for Python | PPT
Train neural networks using AMD GPU and Keras | by Mattia Varile | Towards Data Science
Meet the Innovation of Intel AI Software: Intel® Extension for...
pygpu.gpuarray.GpuArrayException on Theano OpenCL backend · Issue #4965 · keras-team/keras · GitHub
SoyNet, a Fast and Affordable Solution for Inference Optimization - Edge AI and Vision Alliance
