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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Exafunction enhances the efficiency of your deep learning inference tasks, achieving up to a tenfold increase in resource utilization and cost savings. This allows you to concentrate on developing your deep learning application rather than juggling cluster management and performance tuning. In many deep learning scenarios, limitations in CPU, I/O, and network capacities can hinder the optimal use of GPU resources. With Exafunction, GPU code is efficiently migrated to high-utilization remote resources, including cost-effective spot instances, while the core logic operates on a low-cost CPU instance. Proven in demanding applications such as large-scale autonomous vehicle simulations, Exafunction handles intricate custom models, guarantees numerical consistency, and effectively manages thousands of GPUs working simultaneously. It is compatible with leading deep learning frameworks and inference runtimes, ensuring that models and dependencies, including custom operators, are meticulously versioned, so you can trust that you're always obtaining accurate results. This comprehensive approach not only enhances performance but also simplifies the deployment process, allowing developers to focus on innovation instead of infrastructure.

Description

Zipher is an innovative optimization platform that autonomously enhances the performance and cost-effectiveness of workloads on Databricks by removing the need for manual tuning and resource management, all while making real-time adjustments to clusters. Utilizing advanced proprietary machine learning algorithms, Zipher features a unique Spark-aware scaler that actively learns from and profiles workloads to determine the best resource allocations, optimize configurations for each job execution, and fine-tune various settings such as hardware, Spark configurations, and availability zones, thereby maximizing operational efficiency and minimizing waste. The platform continuously tracks changing workloads to modify configurations, refine scheduling, and distribute shared compute resources effectively to adhere to service level agreements (SLAs), while also offering comprehensive cost insights that dissect expenses related to Databricks and cloud services, enabling teams to pinpoint significant cost influencers. Furthermore, Zipher ensures smooth integration with major cloud providers like AWS, Azure, and Google Cloud, and is compatible with popular orchestration and infrastructure-as-code (IaC) tools, making it a versatile solution for various cloud environments. Its ability to adaptively respond to workload changes sets Zipher apart as a crucial tool for organizations striving to optimize their cloud operations.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Apache Airflow
Azure Data Factory
Databricks Data Intelligence Platform
Google Cloud Platform
Microsoft Azure
PyTorch
Slack
TensorFlow
Terraform
dbt

Integrations

Amazon Web Services (AWS)
Apache Airflow
Azure Data Factory
Databricks Data Intelligence Platform
Google Cloud Platform
Microsoft Azure
PyTorch
Slack
TensorFlow
Terraform
dbt

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Exafunction

Website

exafunction.com

Vendor Details

Company Name

Zipher

Founded

2023

Country

United States

Website

zipher.cloud/

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Alternatives

Alternatives

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