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What is Arm DDT?

Arm DDT is recognized as the leading debugger for servers and high-performance computing (HPC), favored by software developers and researchers in diverse fields who are working with applications in C++, C, and Fortran, particularly those employing parallel and threaded processes across various CPU and GPU architectures, including Intel and Arm. Its reputation stems from its powerful ability to automatically detect memory-related problems and divergent behaviors, which leads to outstanding performance across different computational scales. Furthermore, it is crafted to function effortlessly across a multitude of servers and HPC environments while also providing native parallel debugging for Python applications. In addition to its top-notch memory debugging features, Arm DDT excels in supporting C++ and offers thorough debugging capabilities for Fortran, making it a versatile tool for developers. It also includes an offline mode that is ideal for non-interactive debugging, allowing for effective management and visualization of extensive data sets. As a versatile parallel debugger, Arm DDT can be used on its own or integrated into the Arm Forge debug and profile suite, while its intuitive graphical interface significantly enhances usability by automatically identifying memory errors and divergent behaviors across all complexity levels of applications. This all-encompassing tool simplifies the debugging workflow and plays a vital role in optimizing both scientific and engineering software, making it an essential asset for anyone in the field. Additionally, its ability to seamlessly integrate into existing workflows ensures that users can maximize their productivity while maintaining high standards of code quality.

What is Amazon SageMaker Debugger?

Improve machine learning models by capturing real-time training metrics and initiating alerts for any detected anomalies. To reduce both training time and expenses, the training process can automatically stop once the desired accuracy is achieved. Additionally, it is crucial to continuously evaluate and oversee system resource utilization, generating alerts when any limitations are detected to enhance resource efficiency. With the use of Amazon SageMaker Debugger, the troubleshooting process during training can be significantly accelerated, turning what usually takes days into just a few minutes by automatically pinpointing and notifying users about prevalent training challenges, such as extreme gradient values. Alerts can be conveniently accessed through Amazon SageMaker Studio or configured via Amazon CloudWatch. Furthermore, the SageMaker Debugger SDK is specifically crafted to autonomously recognize new types of model-specific errors, encompassing issues related to data sampling, hyperparameter configurations, and values that surpass acceptable thresholds, thereby further strengthening the reliability of your machine learning models. This proactive methodology not only conserves time but also guarantees that your models consistently operate at peak performance levels, ultimately leading to better outcomes and improved overall efficiency.

Media

Media

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Autodesk A360
C
C++
Change Healthcare Data & Analytics
Fortran
Intel Tiber AI Cloud
Jtest
Keras
MXNet
PyTorch
TensorFlow

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Autodesk A360
C
C++
Change Healthcare Data & Analytics
Fortran
Intel Tiber AI Cloud
Jtest
Keras
MXNet
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Arm

Company Location

United Kingdom

Company Website

www.arm.com/products/development-tools/server-and-hpc/forge/ddt

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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