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Snyk is the leader in developer security. We empower the world’s developers to build secure applications and equip security teams to meet the demands of the digital world. Our developer-first approach ensures organizations can secure all of the critical components of their applications from code to cloud, leading to increased developer productivity, revenue growth, customer satisfaction, cost savings and an overall improved security posture. Snyk is a developer security platform that automatically integrates with a developer’s workflow and is purpose-built for security teams to collaborate with their development teams.

You can use your favorite debugging software to locally troubleshoot your Kubernetes services. Telepresence, an open-source tool, allows you to run one service locally and connect it to a remote Kubernetes cluster. Telepresence was initially developed by Ambassador Labs, which creates open-source development tools for Kubernetes such as Ambassador and Forge. We welcome all contributions from the community. You can help us by submitting an issue, pull request or reporting a bug. Join our active Slack group to ask questions or inquire about paid support plans. Telepresence is currently under active development. Register to receive updates and announcements. You can quickly debug locally without waiting for a container to be built/push/deployed. Ability to use their favorite local tools such as debugger, IDE, etc. Ability to run large-scale programs that aren't possible locally.

There's no requirement to modify your coding practices or the methods you use to develop your projects. You can conduct profiling for applications that operate on multiple servers and involve various processes, providing clear insights into potential bottlenecks related to I/O, computational tasks, threading, or multi-process operations. You'll gain a profound understanding of the specific types of processor instructions that impact your overall performance. Additionally, you can monitor memory usage over time, allowing you to identify peak usage points and fluctuations throughout the entire memory landscape. Arm MAP stands out as a uniquely scalable profiler with low overhead, available both as an independent tool and as part of the comprehensive Arm Forge debugging and profiling suite. It is designed to assist developers of server and high-performance computing (HPC) software in speeding up their applications by pinpointing the root causes of sluggish performance. This tool is versatile enough to be employed on everything from multicore Linux workstations to advanced supercomputers. You have the option to profile realistic scenarios that matter the most to you while typically incurring less than 5% in runtime overhead. The user interface is interactive, fostering clarity and ease of use, making it well-suited for both developers and computational scientists alike, enhancing their productivity and efficiency.

Create dependable and optimized code that delivers accurate results across various Server and HPC architectures, utilizing the latest compilers and C++ standards tailored for Intel, 64-bit Arm, AMD, OpenPOWER, and Nvidia GPU platforms. Arm Forge integrates Arm DDT, a premier debugger designed to streamline the debugging process of high-performance applications, with Arm MAP, a respected performance profiler offering essential optimization insights for both native and Python HPC applications, along with Arm Performance Reports that provide sophisticated reporting features. Both Arm DDT and Arm MAP can also be used as independent products, allowing flexibility in application development. This package ensures efficient Linux Server and HPC development while offering comprehensive technical support from Arm specialists. Arm DDT stands out as the preferred debugger for C++, C, or Fortran applications that are parallel or threaded, whether they run on CPUs or GPUs. With its powerful and user-friendly graphical interface, Arm DDT enables users to swiftly identify memory errors and divergent behaviors at any scale, solidifying its reputation as the leading debugger in the realms of research, industry, and academia, making it an invaluable tool for developers. Additionally, its rich feature set fosters an environment conducive to innovation and performance enhancement.

Arm DDT stands out as the premier debugger for servers and high-performance computing (HPC) in research, industry, and educational settings, serving software engineers and scientists who work with C++, C, and Fortran in parallel and threaded environments across both CPUs and GPUs, including those from Intel and Arm. Renowned for its robust capabilities, Arm DDT excels at automatically identifying memory issues and divergent behavior, enabling users to attain exceptional performance across various scales. This versatile tool supports multiple server and HPC architectures, offering seamless cross-platform functionality. Additionally, it provides native parallel debugging for Python applications, ensuring comprehensive support for a range of programming needs. Arm DDT is distinguished by its leading memory debugging features and exceptional support for C++ and Fortran debugging, along with an offline mode that allows for non-interactive debugging sessions. It is also equipped to manage and visualize substantial data sets effectively. Available as a standalone tool or as a component of the Arm Forge debug and profile suite, Arm DDT boasts an intuitive graphical interface that simplifies the process of detecting memory bugs and divergent behaviors across diverse computational scales. This makes it an invaluable resource for engineers and researchers alike, ultimately facilitating the development of high-performance applications.

IDA Pro serves as a powerful disassembler that generates execution maps to represent the binary instructions executed by the processor in a symbolic format, specifically assembly language. With the implementation of advanced techniques, IDA Pro is able to translate machine-executable code into assembly language source code, enhancing the readability of complex code. Additionally, its debugging feature incorporates dynamic analysis, allowing it to support various debugging targets and manage remote applications effectively. The tool's cross-platform debugging capabilities facilitate immediate debugging and provide easy connections to both local and remote processes, while also accommodating 64-bit systems and various connection options. Furthermore, IDA Pro empowers human analysts by allowing them to override its decisions or provide hints, ensuring a more intuitive and efficient analysis of binary code. This flexibility significantly enhances the analyst's ability to interact with the disassembler, making the process of analyzing intricate binaries not only more manageable but also more effective overall.

High-performance computing (HPC) serves as a fundamental element for applications in AI, machine learning, and deep learning. The Intel® oneAPI HPC Toolkit (HPC Kit) equips developers with essential tools to create, analyze, enhance, and expand HPC applications by utilizing the most advanced methods in vectorization, multithreading, multi-node parallelization, and memory management. This toolkit is an essential complement to the Intel® oneAPI Base Toolkit, which is necessary to unlock its complete capabilities. Additionally, it provides users with access to the Intel® Distribution for Python*, the Intel® oneAPI DPC++/C++ compiler, a suite of robust data-centric libraries, and sophisticated analysis tools. You can obtain everything needed to construct, evaluate, and refine your oneAPI projects at no cost. By signing up for an Intel® Developer Cloud account, you gain 120 days of access to the latest Intel® hardware—including CPUs, GPUs, FPGAs—and the full suite of Intel oneAPI tools and frameworks. This seamless experience requires no software downloads, no configuration processes, and no installations, making it incredibly user-friendly for developers at all levels.

AWS ParallelCluster is a free, open-source tool designed for efficient management and deployment of High-Performance Computing (HPC) clusters within the AWS environment. It streamlines the configuration of essential components such as compute nodes, shared filesystems, and job schedulers, while accommodating various instance types and job submission queues. Users have the flexibility to engage with ParallelCluster using a graphical user interface, command-line interface, or API, which allows for customizable cluster setups and oversight. The tool also works seamlessly with job schedulers like AWS Batch and Slurm, making it easier to transition existing HPC workloads to the cloud with minimal adjustments. Users incur no additional costs for the tool itself, only paying for the AWS resources their applications utilize. With AWS ParallelCluster, users can effectively manage their computing needs through a straightforward text file that allows for the modeling, provisioning, and dynamic scaling of necessary resources in a secure and automated fashion. This ease of use significantly enhances productivity and optimizes resource allocation for various computational tasks.

Amazon EC2 UltraClusters allow for the scaling of thousands of GPUs or specialized machine learning accelerators like AWS Trainium, granting users immediate access to supercomputing-level performance. This service opens the door to supercomputing for developers involved in machine learning, generative AI, and high-performance computing, all through a straightforward pay-as-you-go pricing structure that eliminates the need for initial setup or ongoing maintenance expenses. Comprising thousands of accelerated EC2 instances placed within a specific AWS Availability Zone, UltraClusters utilize Elastic Fabric Adapter (EFA) networking within a petabit-scale nonblocking network. Such an architecture not only ensures high-performance networking but also facilitates access to Amazon FSx for Lustre, a fully managed shared storage solution based on a high-performance parallel file system that enables swift processing of large datasets with sub-millisecond latency. Furthermore, EC2 UltraClusters enhance scale-out capabilities for distributed machine learning training and tightly integrated HPC tasks, significantly decreasing training durations while maximizing efficiency. This transformative technology is paving the way for groundbreaking advancements in various computational fields.

The Lustre file system is a parallel, open-source file system designed to cater to the demanding requirements of high-performance computing (HPC) simulation environments often found in leadership class facilities. Whether you are part of our vibrant development community or evaluating Lustre as a potential parallel file system option, you will find extensive resources and support available to aid you. Offering a POSIX-compliant interface, the Lustre file system can efficiently scale to accommodate thousands of clients, manage petabytes of data, and deliver impressive I/O bandwidths exceeding hundreds of gigabytes per second. Its architecture includes essential components such as Metadata Servers (MDS), Metadata Targets (MDT), Object Storage Servers (OSS), Object Server Targets (OST), and Lustre clients. Lustre is specifically engineered to establish a unified, global POSIX-compliant namespace suited for massive computing infrastructures, including some of the largest supercomputing platforms in existence. With its capability to handle hundreds of petabytes of data storage, Lustre stands out as a robust solution for organizations looking to manage extensive datasets effectively. Its versatility and scalability make it a preferable choice for a wide range of applications in scientific research and data-intensive computing.

Arm Allinea Studio is a comprehensive set of tools designed for the development of server and high-performance computing (HPC) applications specifically on Arm architectures. This suite includes compilers and libraries tailored for Arm, as well as tools for debugging and optimization. Among its offerings, the Arm Performance Libraries deliver optimized standard core mathematical libraries that enhance the performance of HPC applications running on Arm processors. These libraries feature routines accessible through both Fortran and C interfaces. Additionally, the Arm Performance Libraries incorporate OpenMP, ensuring a wide range of support across various BLAS, LAPACK, FFT, and sparse routines, ultimately aimed at maximizing performance in multi-processor environments. With these tools, developers can efficiently harness the full potential of Arm-based platforms for their computational needs.

Azure offers high-performance computing (HPC) solutions that drive innovative breakthroughs, tackle intricate challenges, and enhance your resource-heavy tasks. You can create and execute your most demanding applications in the cloud with a comprehensive solution specifically designed for HPC. Experience the benefits of supercomputing capabilities, seamless interoperability, and nearly limitless scalability for compute-heavy tasks through Azure Virtual Machines. Enhance your decision-making processes and advance next-generation AI applications using Azure's top-tier AI and analytics services. Additionally, protect your data and applications while simplifying compliance through robust, multilayered security measures and confidential computing features. This powerful combination ensures that organizations can achieve their computational goals with confidence and efficiency.

SourceDebug is a robust and efficient project-focused programming editor, code explorer, and debugging tool designed to enhance your understanding of code as you work and strategize. It features integrated dynamic analysis for languages such as C/C++ and Objective-C, making it versatile for various coding tasks. With SourceDebug, you can debug applications even when the source code is stored in different locations, ensuring flexibility in your workflow. The application seamlessly combines editing, browsing, compiling, and debugging functionalities for both local and remote projects. This tool is particularly useful for rapidly familiarizing yourself with an existing codebase, enabling a smooth transition to new projects. SourceDebug thoroughly analyzes your project, allowing for effortless navigation and code editing. You can quickly jump to variables, functions, or included files, enhancing productivity. The Smart Bookmark feature is a standout, as it records your browsing position for easy access later. Additionally, it supports debugging through GDB or LLDB-MI over various protocols such as SSH, ADB, Telnet, Rlogin, and Local Cygwin, with GDB server debugging also available. Users can show Quickwatch, Watches, Callstack, Variables, Memory, Breakpoint List, Disassemble, and Thread List as necessary. Furthermore, SourceDebug supports various storage solutions, including SFTP, FTP, and local drives, making it a comprehensive tool for developers. This versatility empowers programmers to tackle complex projects with ease and efficiency.

AWS High Performance Computing (HPC) services enable users to run extensive simulations and deep learning tasks in the cloud, offering nearly limitless computing power, advanced file systems, and high-speed networking capabilities. This comprehensive set of services fosters innovation by providing a diverse array of cloud-based resources, such as machine learning and analytics tools, which facilitate swift design and evaluation of new products. Users can achieve peak operational efficiency thanks to the on-demand nature of these computing resources, allowing them to concentrate on intricate problem-solving without the limitations of conventional infrastructure. AWS HPC offerings feature the Elastic Fabric Adapter (EFA) for optimized low-latency and high-bandwidth networking, AWS Batch for efficient scaling of computing tasks, AWS ParallelCluster for easy cluster setup, and Amazon FSx for delivering high-performance file systems. Collectively, these services create a flexible and scalable ecosystem that is well-suited for a variety of HPC workloads, empowering organizations to push the boundaries of what’s possible in their respective fields. As a result, users can experience greatly enhanced performance and productivity in their computational endeavors.

The Nimbix Supercomputing Suite offers a diverse and secure range of high-performance computing (HPC) solutions available as a service. This innovative model enables users to tap into a comprehensive array of HPC and supercomputing resources, spanning from hardware options to bare metal-as-a-service, facilitating the widespread availability of advanced computing capabilities across both public and private data centers. Through the Nimbix Supercomputing Suite, users gain access to the HyperHub Application Marketplace, which features an extensive selection of over 1,000 applications and workflows designed for high performance. By utilizing dedicated BullSequana HPC servers as bare metal-as-a-service, clients can enjoy superior infrastructure along with the flexibility of on-demand scalability, convenience, and agility. Additionally, the federated supercomputing-as-a-service provides a centralized service console, enabling efficient management of all computing zones and regions within a public or private HPC, AI, and supercomputing federation, thereby streamlining operations and enhancing productivity. This comprehensive suite empowers organizations to drive innovation and optimize performance across various computational tasks.

The Ansys HPC software suite allows users to leverage modern multicore processors to conduct a greater number of simulations in a shorter timeframe. These simulations can achieve unprecedented levels of complexity, size, and accuracy thanks to high-performance computing (HPC) capabilities. Ansys provides a range of HPC licensing options that enable scalability, accommodating everything from single-user setups for basic parallel processing to extensive configurations that support nearly limitless parallel processing power. For larger teams, Ansys ensures the ability to execute highly scalable, multiple parallel processing simulations to tackle the most demanding projects. In addition to its parallel computing capabilities, Ansys also delivers parametric computing solutions, allowing for a deeper exploration of various design parameters—including dimensions, weight, shape, materials, and mechanical properties—during the early stages of product development. This comprehensive approach not only enhances simulation efficiency but also significantly optimizes the design process.

Quickly identify performance issues and gain insights into the workings of a complex C/C++ application using Orbit, a standalone profiling and debugging tool designed for both Windows and Linux environments. This tool is specifically engineered to assist developers in comprehending and visualizing the execution flow within intricate applications. By providing an overarching perspective on the internal operations, Orbit enhances the developer's grasp of complex systems, enabling them to swiftly pinpoint performance bottlenecks. The tool seamlessly operates with any C/C++ application, provided it has access to the Pdb file, allowing you to initiate profiling immediately after downloading Orbit. Upon launch, Orbit integrates itself within the target process, hooking into specific functions, and is effective even with highly optimized final or shipping builds. Its sampling feature is particularly beneficial when starting your investigation, as it is fast, reliable, and continuously active. Orbit optimizes the profiling process by combining sampling techniques with dynamic instrumentation, ensuring a more efficient workflow for developers seeking to enhance application performance. Additionally, the ability to visualize execution paths greatly aids in understanding how different components interact within the system.

BMC Compuware Xpediter comprises a suite of debugging and interactive analysis tools designed for COBOL, Assembler, PL/I, and C programming languages, enabling developers to swiftly grasp application structures, implement modifications, and resolve issues securely, even when they lack familiarity with the original codebase. This platform allows developers to initiate interactive test sessions with ease, facilitating a smoother transition of applications into production while boosting their confidence in the process. Users can execute code line by line, gaining control over every facet of program execution and associated data. The inclusion of Code Coverage provides evidence of execution and valuable metrics for applications across various platforms. Additionally, developers can utilize Abend-AID's diagnostic features directly within their debugging sessions. The integration with Topaz for Program Analysis offers a visual representation of the source code, enhancing the debugging experience. Furthermore, Topaz for Total Test aids in creating a thorough collection of automated virtualized test cases, ensuring comprehensive testing. It even allows for the interception and debugging of mainframe transactions that are triggered remotely, showcasing its versatility in different environments. By utilizing these advanced tools, developers can significantly enhance their productivity and application reliability.

AWS Parallel Computing Service (AWS PCS) is a fully managed service designed to facilitate the execution and scaling of high-performance computing tasks while also aiding in the development of scientific and engineering models using Slurm on AWS. This service allows users to create comprehensive and adaptable environments that seamlessly combine computing, storage, networking, and visualization tools, enabling them to concentrate on their research and innovative projects without the hassle of managing the underlying infrastructure. With features like automated updates and integrated observability, AWS PCS significantly improves the operations and upkeep of computing clusters. Users can easily construct and launch scalable, dependable, and secure HPC clusters via the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. The versatility of the service supports a wide range of applications, including tightly coupled workloads such as computer-aided engineering, high-throughput computing for tasks like genomics analysis, GPU-accelerated computing, and specialized silicon solutions like AWS Trainium and AWS Inferentia. Overall, AWS PCS empowers researchers and engineers to harness advanced computing capabilities without needing to worry about the complexities of infrastructure setup and maintenance.

HPE Performance Cluster Manager (HPCM) offers a cohesive system management solution tailored for Linux®-based high-performance computing (HPC) clusters. This software facilitates comprehensive provisioning, management, and monitoring capabilities for clusters that can extend to Exascale-sized supercomputers. HPCM streamlines the initial setup from bare-metal, provides extensive hardware monitoring and management options, oversees image management, handles software updates, manages power efficiently, and ensures overall cluster health. Moreover, it simplifies the scaling process for HPC clusters and integrates seamlessly with numerous third-party tools to enhance workload management. By employing HPE Performance Cluster Manager, organizations can significantly reduce the administrative burden associated with HPC systems, ultimately leading to lowered total ownership costs and enhanced productivity, all while maximizing the return on their hardware investments. As a result, HPCM not only fosters operational efficiency but also supports organizations in achieving their computational goals effectively.

Amazon S3 Express One Zone is designed as a high-performance storage class that operates within a single Availability Zone, ensuring reliable access to frequently used data and meeting the demands of latency-sensitive applications with single-digit millisecond response times. It boasts data retrieval speeds that can be up to 10 times quicker, alongside request costs that can be reduced by as much as 50% compared to the S3 Standard class. Users have the flexibility to choose a particular AWS Availability Zone in an AWS Region for their data, which enables the co-location of storage and computing resources, ultimately enhancing performance and reducing compute expenses while expediting workloads. The data is managed within a specialized bucket type known as an S3 directory bucket, which can handle hundreds of thousands of requests every second efficiently. Furthermore, S3 Express One Zone can seamlessly integrate with services like Amazon SageMaker Model Training, Amazon Athena, Amazon EMR, and AWS Glue Data Catalog, thereby speeding up both machine learning and analytical tasks. This combination of features makes S3 Express One Zone an attractive option for businesses looking to optimize their data management and processing capabilities.

The NVIDIA DGX Cloud provides an AI infrastructure as a service that simplifies the deployment of large-scale AI models and accelerates innovation. By offering a comprehensive suite of tools for machine learning, deep learning, and HPC, this platform enables organizations to run their AI workloads efficiently on the cloud. With seamless integration into major cloud services, it offers the scalability, performance, and flexibility necessary for tackling complex AI challenges, all while eliminating the need for managing on-premise hardware.

Elevate your log management with Honeycomb, a platform designed specifically for contemporary development teams aiming to gain insights into application performance while enhancing log management capabilities. With Honeycomb’s rapid query functionality, you can uncover hidden issues across your system’s logs, metrics, and traces, utilizing interactive charts that provide an in-depth analysis of raw data that boasts high cardinality. You can set up Service Level Objectives (SLOs) that reflect user priorities, which helps in reducing unnecessary alerts and allows you to focus on what truly matters. By minimizing on-call responsibilities and speeding up code deployment, you can ensure customer satisfaction remains high. Identify the root causes of performance issues, optimize your code efficiently, and view your production environment in high resolution. Our SLOs will alert you when customers experience difficulties, enabling you to swiftly investigate the underlying problems—all from a single interface. Additionally, the Query Builder empowers you to dissect your data effortlessly, allowing you to visualize behavioral trends for both individual users and services, organized by various dimensions for enhanced analytical insights. This comprehensive approach ensures that your team can respond proactively to performance challenges while refining the overall user experience.

Sourcery CodeBench offers a comprehensive suite of tools designed to assist embedded software engineers in the effective development and enhancement of software across numerous targets and sectors, such as Automotive, Connectivity, Graphics, and Video applications. This suite extends beyond a mere compiler, equipping developers with robust open-source C/C++ development tools that facilitate the building, debugging, analysis, and optimization of embedded software within intricate heterogeneous architectures like Arm, IA32, MIPS, and Power Architectures. The integrated Eclipse-based IDE allows for tailored workspace configuration and efficient project management. Additionally, it features an advanced source code editor that includes syntax highlighting for improved readability. To further support custom hardware implementations, the Board Builder tool automatically creates linker scripts, debug configuration files, and startup code based on the specific memory layout of the board, streamlining the setup process for developers. Overall, Sourcery CodeBench significantly enhances productivity and efficiency for engineers working in embedded systems.

Defang is a developer-focused platform designed to streamline the development, deployment, and debugging of cloud applications. Utilizing AI-driven tools, Defang empowers developers to quickly evolve their concepts into fully operational applications hosted on their selected cloud services. The platform accommodates various programming languages such as Go, JavaScript, and Python, enabling users to kickstart their projects with example templates or create outlines through natural language instructions. With just a single command, Defang automates the building and deployment processes, managing configurations related to computing, storage, load balancing, networking, logging, and security seamlessly. The Defang Command Line Interface (CLI) enhances user interaction with the platform, providing installation methods through shell scripts, Homebrew, Winget, Nix, or direct downloads. Developers can specify their services using compose.yaml files, which Defang leverages to facilitate application deployment in the cloud. Overall, this platform significantly reduces the complexity traditionally associated with cloud application development, making it more accessible for developers at all skill levels.

Kaption stands out as the premier analytics and feedback platform driven by artificial intelligence, specifically designed for digital marketers. Gain the critical insights necessary to enhance your digital presence and propel your business forward. By removing uncertainty, you can understand the reasons behind user behavior and iterate your strategies at a much quicker pace. One of the most effective ways to influence your audience is to perceive your offerings from their perspective. Have you considered how users navigate your website? With Kaption, you can map out the user journey and identify any obstacles encountered along the way. The path to excellence is paved with accurate information; without data, you are merely relying on luck or making mistakes. Direct your energies towards effective conversion and monitoring strategies. Take advantage of complimentary heatmap analytics to analyze user interaction with every component of your site and its impact on their actions. Identify where users face challenges, boost your conversion rates, and resolve product issues more swiftly with intelligent metadata insights. By doing so, you can ensure that your marketing efforts are both informed and effective.

QumulusAI provides unparalleled supercomputing capabilities, merging scalable high-performance computing (HPC) with autonomous data centers to eliminate bottlenecks and propel the advancement of AI. By democratizing access to AI supercomputing, QumulusAI dismantles the limitations imposed by traditional HPC and offers the scalable, high-performance solutions that modern AI applications require now and in the future. With no virtualization latency and no disruptive neighbors, users gain dedicated, direct access to AI servers that are fine-tuned with the latest NVIDIA GPUs (H200) and cutting-edge Intel/AMD CPUs. Unlike legacy providers that utilize a generic approach, QumulusAI customizes HPC infrastructure to align specifically with your unique workloads. Our partnership extends through every phase—from design and deployment to continuous optimization—ensuring that your AI initiatives receive precisely what they need at every stage of development. We maintain ownership of the entire technology stack, which translates to superior performance, enhanced control, and more predictable expenses compared to other providers that rely on third-party collaborations. This comprehensive approach positions QumulusAI as a leader in the supercomputing space, ready to adapt to the evolving demands of your projects.

OpenText Functional Testing Lab for Mobile and Web offers enterprises a scalable, cloud-based digital lab that centralizes real device and browser testing for mobile and web applications. Developers and testers can remotely access a diverse range of real devices, emulators, and cloud browsers to develop, debug, test, and monitor applications from any location, enhancing team productivity. The platform supports flexible scaling to meet fluctuating testing demands, eliminating the need for costly device purchases and maintenance. It also simplifies cloud browser testing by provisioning browsers on demand, removing the overhead of managing physical infrastructure. AI-driven automation enhances efficiency and resilience by streamlining workflows and adapting to testing changes rapidly. Security and privacy features ensure compliance with industry standards and protect sensitive data throughout testing processes. The solution integrates smoothly with open-source testing tools like Appium and Selenium, providing a robust testing ecosystem. Overall, it enables organizations to deliver higher-quality applications faster and with greater confidence.

High-performance tasks associated with data-heavy AI, IoT, and HPC workloads have traditionally relied on costly, top-tier processors or accelerators like Graphics Processing Units (GPUs) to function optimally. Additionally, organizations utilizing cloud-based platforms for demanding computational tasks frequently encounter trade-offs that can be less than ideal. For instance, the outdated nature of processors and hardware in cloud infrastructures often fails to align with the latest software applications, while also raising concerns over excessive energy consumption and environmental implications. Furthermore, users often find certain features of cloud services to be cumbersome and challenging, which hampers their ability to create tailored cloud solutions that meet specific business requirements. This difficulty in achieving a perfect balance can lead to complications in identifying appropriate billing structures and obtaining adequate support for their unique needs. Ultimately, these issues highlight the pressing need for more adaptable and efficient cloud solutions in today's technology landscape.

The NVIDIA HPC Software Development Kit (SDK) offers a comprehensive suite of reliable compilers, libraries, and software tools that are crucial for enhancing developer efficiency as well as the performance and adaptability of HPC applications. This SDK includes C, C++, and Fortran compilers that facilitate GPU acceleration for HPC modeling and simulation applications through standard C++ and Fortran, as well as OpenACC® directives and CUDA®. Additionally, GPU-accelerated mathematical libraries boost the efficiency of widely used HPC algorithms, while optimized communication libraries support standards-based multi-GPU and scalable systems programming. The inclusion of performance profiling and debugging tools streamlines the process of porting and optimizing HPC applications, and containerization tools ensure straightforward deployment whether on-premises or in cloud environments. Furthermore, with compatibility for NVIDIA GPUs and various CPU architectures like Arm, OpenPOWER, or x86-64 running on Linux, the HPC SDK equips developers with all the necessary resources to create high-performance GPU-accelerated HPC applications effectively. Ultimately, this robust toolkit is indispensable for anyone looking to push the boundaries of high-performance computing.

Bright Cluster Manager offers a variety of machine learning frameworks including Torch, Tensorflow and Tensorflow to simplify your deep-learning projects. Bright offers a selection the most popular Machine Learning libraries that can be used to access datasets. These include MLPython and NVIDIA CUDA Deep Neural Network Library (cuDNN), Deep Learning GPU Trainer System (DIGITS), CaffeOnSpark (a Spark package that allows deep learning), and MLPython. Bright makes it easy to find, configure, and deploy all the necessary components to run these deep learning libraries and frameworks. There are over 400MB of Python modules to support machine learning packages. We also include the NVIDIA hardware drivers and CUDA (parallel computer platform API) drivers, CUB(CUDA building blocks), NCCL (library standard collective communication routines).

Accelerate computational tasks such as those found in machine learning and high-performance computing (HPC) with a diverse array of GPUs suited for various performance levels and budget constraints. With adaptable pricing and customizable machines, you can fine-tune your setup to enhance your workload efficiency. Google Cloud offers high-performance GPUs ideal for machine learning, scientific analyses, and 3D rendering. The selection includes NVIDIA K80, P100, P4, T4, V100, and A100 GPUs, providing a spectrum of computing options tailored to meet different cost and performance requirements. You can effectively balance processor power, memory capacity, high-speed storage, and up to eight GPUs per instance to suit your specific workload needs. Enjoy the advantage of per-second billing, ensuring you only pay for the resources consumed during usage. Leverage GPU capabilities on Google Cloud Platform, where you benefit from cutting-edge storage, networking, and data analytics solutions. Compute Engine allows you to easily integrate GPUs into your virtual machine instances, offering an efficient way to enhance processing power. Explore the potential uses of GPUs and discover the various types of GPU hardware available to elevate your computational projects.

Amazon EC2 P4d instances are designed for optimal performance in machine learning training and high-performance computing (HPC) applications within the cloud environment. Equipped with NVIDIA A100 Tensor Core GPUs, these instances provide exceptional throughput and low-latency networking capabilities, boasting 400 Gbps instance networking. P4d instances are remarkably cost-effective, offering up to a 60% reduction in expenses for training machine learning models, while also delivering an impressive 2.5 times better performance for deep learning tasks compared to the older P3 and P3dn models. They are deployed within expansive clusters known as Amazon EC2 UltraClusters, which allow for the seamless integration of high-performance computing, networking, and storage resources. This flexibility enables users to scale their operations from a handful to thousands of NVIDIA A100 GPUs depending on their specific project requirements. Researchers, data scientists, and developers can leverage P4d instances to train machine learning models for diverse applications, including natural language processing, object detection and classification, and recommendation systems, in addition to executing HPC tasks such as pharmaceutical discovery and other complex computations. These capabilities collectively empower teams to innovate and accelerate their projects with greater efficiency and effectiveness.

TrinityX is a cluster management solution that is open source and developed by ClusterVision, aimed at ensuring continuous monitoring for environments focused on High-Performance Computing (HPC) and Artificial Intelligence (AI). It delivers a robust support system that adheres to service level agreements (SLAs), enabling researchers to concentrate on their work without the burden of managing intricate technologies such as Linux, SLURM, CUDA, InfiniBand, Lustre, and Open OnDemand. By providing an easy-to-use interface, TrinityX simplifies the process of cluster setup, guiding users through each phase to configure clusters for various applications including container orchestration, conventional HPC, and InfiniBand/RDMA configurations. Utilizing the BitTorrent protocol, it facilitates the swift deployment of AI and HPC nodes, allowing for configurations to be completed in mere minutes. Additionally, the platform boasts a detailed dashboard that presents real-time data on cluster performance metrics, resource usage, and workload distribution, which helps users quickly identify potential issues and optimize resource distribution effectively. This empowers teams to make informed decisions that enhance productivity and operational efficiency within their computational environments.

Amazon's Elastic Compute Cloud (EC2) offers P5 instances that utilize NVIDIA H100 Tensor Core GPUs, alongside P5e and P5en instances featuring NVIDIA H200 Tensor Core GPUs, ensuring unmatched performance for deep learning and high-performance computing tasks. With these advanced instances, you can reduce the time to achieve results by as much as four times compared to earlier GPU-based EC2 offerings, while also cutting ML model training costs by up to 40%. This capability enables faster iteration on solutions, allowing businesses to reach the market more efficiently. P5, P5e, and P5en instances are ideal for training and deploying sophisticated large language models and diffusion models that drive the most intensive generative AI applications, which encompass areas like question-answering, code generation, video and image creation, and speech recognition. Furthermore, these instances can also support large-scale deployment of high-performance computing applications, facilitating advancements in fields such as pharmaceutical discovery, ultimately transforming how research and development are conducted in the industry.

The Elastic Fabric Adapter (EFA) serves as a specialized network interface for Amazon EC2 instances, allowing users to efficiently run applications that demand high inter-node communication at scale within the AWS environment. By utilizing a custom-designed operating system (OS) that circumvents traditional hardware interfaces, EFA significantly boosts the performance of communications between instances, which is essential for effectively scaling such applications. This technology facilitates the scaling of High-Performance Computing (HPC) applications that utilize the Message Passing Interface (MPI) and Machine Learning (ML) applications that rely on the NVIDIA Collective Communications Library (NCCL) to thousands of CPUs or GPUs. Consequently, users can achieve the same high application performance found in on-premises HPC clusters while benefiting from the flexible and on-demand nature of the AWS cloud infrastructure. EFA can be activated as an optional feature for EC2 networking without incurring any extra charges, making it accessible for a wide range of use cases. Additionally, it seamlessly integrates with the most popular interfaces, APIs, and libraries for inter-node communication needs, enhancing its utility for diverse applications.

Amazon EC2 G4 instances are specifically designed to enhance the performance of machine learning inference and applications that require high graphics capabilities. Users can select between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad) according to their requirements. The G4dn instances combine NVIDIA T4 GPUs with bespoke Intel Cascade Lake CPUs, ensuring an optimal mix of computational power, memory, and networking bandwidth. These instances are well-suited for tasks such as deploying machine learning models, video transcoding, game streaming, and rendering graphics. On the other hand, G4ad instances, equipped with AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, offer a budget-friendly option for handling graphics-intensive workloads. Both instance types utilize Amazon Elastic Inference, which permits users to add economical GPU-powered inference acceleration to Amazon EC2, thereby lowering costs associated with deep learning inference. They come in a range of sizes tailored to meet diverse performance demands and seamlessly integrate with various AWS services, including Amazon SageMaker, Amazon ECS, and Amazon EKS. Additionally, this versatility makes G4 instances an attractive choice for organizations looking to leverage cloud-based machine learning and graphics processing capabilities.

Kombyne™ represents a cutting-edge Software as a Service (SaaS) tool designed for high-performance computing (HPC) workflows, originally tailored for clients in sectors such as defense, automotive, aerospace, and academic research. This platform empowers users to access a diverse array of workflow solutions specifically for HPC computational fluid dynamics (CFD) tasks, encompassing features like on-the-fly extract generation, rendering capabilities, and simulation steering options. Users can benefit from interactive monitoring and control functionalities, all while ensuring minimal disruption to simulations and eliminating reliance on VTK. By employing extract workflows, the necessity for handling large files is significantly reduced, allowing for real-time visualization. The system incorporates an in-transit workflow that utilizes a distinct process to swiftly receive data from the solver code, enabling visualization and analysis without hindering the operation of the running solver. This specialized process, referred to as an endpoint, facilitates the direct output of extracts, cutting planes, or point samples useful for data science, in addition to rendering images. Furthermore, the Endpoint serves as a conduit to widely-used visualization software, enhancing the overall usability and integration of the tool within various workflows. With its versatile features and ease of use, Kombyne™ is set to revolutionize the way HPC tasks are managed and executed across multiple industries.

ActiveState delivers Intelligent Remediation for vulnerability management, which enables DevSecOps teams to not only identify vulnerabilities in open source packages, but also to automatically prioritize, remediate, and deploy fixes into production without breaking changes, ensuring that applications are truly secured. We do this by helping you: - Understand your vulnerability blast radius so you can see every vulnerabilities’ true impact across your organization. This is driven by our proprietary catalog of 40M+ open source components that’s been built and tested for over 25 years. - Intelligently prioritize remediations so you can turn risks into action. We help teams move away from alert overload with AI-powered analysis that detects breaking changes, streamlines remediation workflows, and accelerates security processes. - Precisely remediate what matters - unlike other solutions, ActiveState doesn’t just suggest what you should do, we enable you to deploy fixed artifacts or document exceptions so you can truly drive down vulnerabilities and secure your software supply chain. The ActiveState platform centers on open source languages packaged as runtimes that can be deployed in various form factors. Low-to-no CVE container images are also available for plug-in and play needs.

Black Duck, a segment of the Synopsys Software Integrity Group, stands out as a prominent provider of application security testing (AST) solutions. Their extensive array of offerings encompasses tools for static analysis, software composition analysis (SCA), dynamic analysis, and interactive analysis, which assist organizations in detecting and addressing security vulnerabilities throughout the software development life cycle. By streamlining the identification and management of open-source software, Black Duck guarantees adherence to security and licensing regulations. Their solutions are meticulously crafted to enable organizations to foster trust in their software while effectively managing application security, quality, and compliance risks at a pace that aligns with business demands. With Black Duck, businesses are equipped to innovate with security in mind, delivering software solutions confidently and efficiently. Furthermore, their commitment to continuous improvement ensures that clients remain ahead of emerging security challenges in a rapidly evolving technological landscape.

Sonatype Auditor simplifies the process of managing open-source security by automatically generating Software Bills of Materials (SBOM) and identifying risks associated with third-party applications. It provides real-time monitoring of open-source components, detecting vulnerabilities and license violations. By offering actionable insights and remediation guidance, Sonatype Auditor helps organizations secure their software supply chains while ensuring regulatory compliance. With continuous scanning and policy enforcement, it enables businesses to maintain control over their open-source usage and reduce security threats.

CodeSonar uses a unified dataflow with symbolic execution analysis to examine the entire application's computations. CodeSonar's static analyze engine is extremely deep and does not rely on pattern matching or similar approximations. It finds 3-5 times more defects than other static analysis tools. SAST tools are able to be easily integrated into any team's software development process, unlike many other tools such as testing tools and compilers. SAST technologies such as CodeSonar attach to existing build environments to add analysis information. CodeSonar works in the same way as a compiler. However, CodeSonar creates an abstraction model of your entire program, instead of creating object codes. CodeSonar's symbolic execution engine analyzes the derived model and makes connections between them.

Thundra helps application teams to develop, debug, test, and monitor modern microservices on the cloud. By offering everything from automated instrumentation to cloud app debugging and test optimization in a single platform, Thundra eliminates the need for multiple tools for pre-production & production environments. Thundra offers 2 products: Thundra Foresight, to help you monitor & troubleshoot your CI workflows & tests. The second product is Thundra APM, which is an application performance monitoring for serverless and containers.

Modern software development must be as fast as the business. The modern AppSec toolbox lacks integration, which creates complexity that slows down software development life cycles. Contrast reduces the complexity that hinders today's development teams. Legacy AppSec uses a single-size-fits all approach to vulnerability detection and remediation that is inefficient, costly, and expensive. Contrast automatically applies the most efficient analysis and remediation technique, greatly improving efficiency and effectiveness. Separate AppSec tools can create silos that hinder the collection of actionable intelligence across an application attack surface. Contrast provides centralized observability, which is crucial for managing risks and capitalizing upon operational efficiencies. This is both for security and development teams. Contrast Scan is a pipeline native product that delivers the speed, accuracy and integration required for modern software development.

Inspector is a powerful tool designed for monitoring code execution, assisting software developers in the automatic detection of errors and performance bottlenecks. It efficiently traces applications regardless of their scale, allowing developers to address issues proactively before they impact customers, all while maintaining predictable and low debugging costs. By using Inspector, teams can enhance their development process and ensure a smoother user experience.