Fabric for Deep Learning (FfDL)
Fabric for Deep Learning (FfDL) offers an efficient platform for running popular deep learning frameworks like TensorFlow and PyTorch as a service on Kubernetes. Its microservices architecture enhances scalability and fault tolerance, enabling independent development and deployment of components, and facilitating rapid learning from large datasets across distributed compute nodes.
Top Fabric for Deep Learning (FfDL) Alternatives
MXNet
MXNet is an open-source deep learning framework designed for both research prototyping and production deployment.
Intel Deep Learning Training Tool
The Intel Deep Learning Training Tool offers learners a robust foundation in deep learning techniques tailored for modern Intel® architecture.
NVIDIA GPU-Optimized AMI
The NVIDIA GPU-Optimized AMI is a virtual machine image designed to accelerate GPU-accelerated workloads in machine learning, deep learning, data science, and HPC.
NVIDIA DIGITS
NVIDIA DIGITS is an advanced deep learning software tailored for life sciences research, offering a fully managed AI platform across leading cloud environments.
Amazon EC2 P5 Instances
Amazon EC2 P5 instances, equipped with NVIDIA H100 and H200 Tensor Core GPUs, deliver unparalleled performance for deep learning and high-performance computing.
NVIDIA GPU Cloud (NGC)
NVIDIA GPU Cloud (NGC) is an advanced AI platform tailored for life sciences research.
Amazon EC2 P4 Instances
Utilizing NVIDIA A100 Tensor Core GPUs, these instances achieve remarkable throughput and low-latency networking at...
NVIDIA NGC
It provides an array of tools, including SDKs, pre-trained AI models, Jupyter Notebooks, and model...
Amazon EC2 G5 Instances
Equipped with up to 8 A10G Tensor Core GPUs and advanced storage, they optimize training...
VisionPro Deep Learning
It excels in defect detection, assembly verification, and character reading...
Google Cloud Deep Learning VM Image
Each image includes essential frameworks such as TensorFlow and PyTorch, along with the latest AI...
Ray
Designed for developers, it enables seamless scaling of Python code for diverse AI applications, from...
Google Deep Learning Containers
Designed for rapid prototyping and deployment, they enable seamless development across various Google Cloud services...
DeepSpeed
It seamlessly wraps any PyTorch model, managing distributed training, mixed precision, and dynamic learning rate...
MEGA
It features end-to-end encryption, secure global access, secure collaboration, up to 4TB storage, mobile apps...
Top Fabric for Deep Learning (FfDL) Features
- Consistent framework service
- Microservices architecture
- Kubernetes orchestration
- Scalable deep learning
- Fault-tolerant design
- Independent component upgrades
- Stateless components
- Simplified component interactions
- Efficient resource utilization
- Large data handling
- Enhanced training speed
- Easy deployment process
- Multi-framework support
- User-friendly interface
- Robust error isolation
- Integrates with popular frameworks
- Continuous integration capabilities
- Automated scaling features
- Comprehensive monitoring tools
- Community-driven enhancements
