Tenstorrent DevCloud Description
Tenstorrent DevCloud was created to allow people to test their models on our servers, without having to purchase our hardware. Tenstorrent AI is being built in the cloud to allow programmers to test our AI solutions. After logging in, your first login is free. You can then connect with our team to better assess your needs. Tenstorrent is a group of motivated and competent people who have come together to create the best computing platform for AI/software 2.0. Tenstorrent is a new-generation computing company that aims to address the rapidly increasing computing needs for software 2.0. Tenstorrent is based in Toronto, Canada. It brings together experts in the fields of computer architecture, basic design and neural network compilers. ur processors have been optimized for neural network training and inference. They can also perform other types of parallel computation. Tenstorrent processors are made up of a grid consisting of Tensix cores.
Tenstorrent DevCloud Alternatives
AWS Neuron
It supports high-performance learning on AWS Trainium based Amazon Elastic Compute Cloud Trn1 instances. It supports low-latency and high-performance inference for model deployment on AWS Inferentia based Amazon EC2 Inf1 and AWS Inferentia2-based Amazon EC2 Inf2 instance. Neuron allows you to use popular frameworks such as TensorFlow or PyTorch and train and deploy machine-learning (ML) models using Amazon EC2 Trn1, inf1, and inf2 instances without requiring vendor-specific solutions. AWS Neuron SDK is natively integrated into PyTorch and TensorFlow, and supports Inferentia, Trainium, and other accelerators. This integration allows you to continue using your existing workflows within these popular frameworks, and get started by changing only a few lines. The Neuron SDK provides libraries for distributed model training such as Megatron LM and PyTorch Fully Sharded Data Parallel (FSDP).
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IBM Watson Machine Learning Accelerator
Your deep learning workload can be accelerated. AI model training and inference can speed up your time to value. Deep learning is becoming more popular as enterprises adopt it to gain and scale insight through speech recognition and natural language processing. Deep learning can read text, images and video at scale and generate patterns for recommendation engines. It can also model financial risk and detect anomalies. Due to the sheer number of layers and volumes of data required to train neural networks, it has been necessary to use high computational power. Businesses are finding it difficult to demonstrate results from deep learning experiments that were implemented in silos.
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Google Cloud Inference API
Time-series analysis is crucial for many companies' day-to-day operations. The most popular uses include analyzing foot traffic and conversions for retailers, detecting data abnormalities, identifying correlations over sensor data, and generating high-quality suggestions. Cloud Inference API Alpha allows you to gather insights from your time-series data in real-time. You can get all the information you need to understand your API query results, including the groups of events examined, the number and background probabilities of each event returned. You can stream data in real time, which makes it possible to calculate correlations for real events. Rely on Google Cloud's entire infrastructure and defense-in depth approach to security, which has been innovating for over 15 years via consumer apps. Cloud Inference API integrates seamlessly with other Google Cloud Storage services.
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Amazon EC2 Capacity Blocks for ML
Amazon EC2 capacity blocks for ML allow you to reserve accelerated compute instance in Amazon EC2 UltraClusters that are dedicated to machine learning workloads. This service supports Amazon EC2 P5en instances powered by NVIDIA Tensor Core GPUs H200, H100 and A100, as well Trn2 and TRn1 instances powered AWS Trainium. You can reserve these instances up to six months ahead of time in cluster sizes from one to sixty instances (512 GPUs, or 1,024 Trainium chip), providing flexibility for ML workloads. Reservations can be placed up to 8 weeks in advance. Capacity Blocks can be co-located in Amazon EC2 UltraClusters to provide low-latency and high-throughput connectivity for efficient distributed training. This setup provides predictable access to high performance computing resources. It allows you to plan ML application development confidently, run tests, build prototypes and accommodate future surges of demand for ML applications.
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Company Details
Company:
Tenstorrent
Headquarters:
Canada
Website:
tenstorrent.com/devcloud/
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