Multi 1-4

[Malka Sedano]

Incomplex real-time systems, unexpected time spent on hunting for sporadic and deeply buried bugs or finding performance bottlenecks can take weeks or even months, potentially risking an on-time product launch.

History viewer displays the last few seconds, minutes or days of program execution across complex heterogenous multicore systems with a natural and intuitive GUI. For the first time you now have a clear, complete view into a murky hardware and software system. You can zoom deeply into processor behavior at the micro-second level or zoom out to see system behavior spanning minutes and days. This new kind of visibility empowers you to find difficult bugs in seconds, see hidden bottlenecks and dependencies, and analyze execution times.

By automatically capturing actual program execution data TimeMachine enables the Debugger to run, step and debug code backward to any problem area shown in History. It also powers other tools such as the Profiler.

Clean code is less likely to contain errors and is easier to test, understand, and modify. All of these factors contribute to fewer bugs and greater reliability. Green Hills optimizing compilers enable enforcement of clean coding conventions defined by industry standards such as the MISRA 2012 and 2004 coding standards, which include more than one hundred rules for safe programming. You can also elect to enforce a customized subset of these rules to meet specific requirements.

The MULTI Debugger is a powerful tool for examining, monitoring, and changing source code running on complex heterogenous multicore target processors and simulators. When TimeMachine is used, it can even run backward in time. The Debugger is seamlessly integrated with other tools within MULTI and can be invoked by clicking inside various MULTI tools such as the History viewer.

When you debug a multitasking application on an OS like INTEGRITY or Linux, MULTI can interact with the multiple tasks in run-mode, freeze-mode, or both modes simultaneously. In run-mode, the operating system kernel continues to run as you halt and examine individual tasks. In freeze-mode, the entire target system stops when you examine tasks.

Key among multicore debugging features is synchronous run control, which halts all cores as a unit when any core encounters a debugging condition. For instance, when a core hits a breakpoint the target list clearly shows:

MULTI for Linux brings advanced debugging to engineers developing embedded Linux software. It dramatically improves their productivity and helps them bring a more reliable, higher-performing product to market faster.

Along with the Builder, the seamlessly-integrated Project Manager, Editor, Flash Programmer, and Instruction Set Simulator that in their own ways help you spend less time on build management and more on your code.

Generate faster, smaller code

Compilers are the essential ingredient to leverage processor performance and the Green Hills C/C++ optimizing compilers are the best in the industry. On the widely-accepted EEMBC benchmarks for embedded processors the Green Hills Compilers consistently outperform competing compilers to generate the fastest and smallest code for 32- and 64-bit processors.

Open enrollment training

Teams with smaller training budgets can attend our popular open-enrollment courses at scheduled locations around the world. These classes are also perfect for new hires who have just joined a team that has already completed a Green Hills Software training class.

The Multi-Resolution Land Characteristics (MRLC) consortium is a group of federal agencies who coordinate and generate consistent and relevant land cover information at the national scale for a wide variety of environmental, land management, and modeling applications. The creation of this consortium has resulted in the mapping of the lower 48 United States, Hawaii, Alaska and Puerto Rico into a comprehensive land cover product termed, the National Land Cover Database (NLCD), from decadal Landsat satellite imagery and other supplementary datasets.

MRLC hosts land cover and land condition data from various sources, including NLCD and Rangeland Condition Monitoring Assessment and Projection (RCMAP) time-series, Ecological Potential, and projections of future fractional rangeland components. Data are offered for download, as WMS services, and in applications.

The U.S. Geological Survey (USGS), in collaboration with the MRLC consortium and Bureau of Land Management (BLM), is pleased to announce the availability of a new generation of Rangeland, Condition, Monitoring, Assessment, and Projection (RCMAP) fractional component data spanning a 1985-2023 time-series. The RCMAP product suite consists of ten components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height (new to this generation). Several enhancements were made to the RCMAP process relative to prior generations. First, we revised the high-resolution training using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. We further improved our training database by incorporating additional datasets. Next, we improved our Landsat compositing approach to better capture the range of conditions from across each year and through time. These composites are based on Collection 2 Landsat data with improved geolocation accuracy and dynamic range.

NLCD products can be explored and/or downloaded from multiple outlets, based on your specific application. If you are a user looking for bulk download options of the entire suite of products, the website includes direct access to the source data and metadata. NLCD is also available in the MRLC NLCD Viewer web application, a dynamic platform for data visualization, side-by-side image analysis and comparisons, and a custom tool enabling users to select a region of interest for download. Local class by class analysis between years is also available at the MRLC EVA Tool (mrlc.gov)

The United States Geological Survey (USGS), in collaboration with the Multi-resolution Landscape Consortium (MRLC), has provided the community with the National Land Cover Database (NLCD), a detailed land cover database for more than 30 years. To produce the next generation of USGS land cover, with moderate thematic detail at low latency and annual frequency, research is well underway for single stream land cover products. In the initial 2024 product release, users can expect Anderson Level II type land cover classes (for example, the 16 land cover categories used in the current NLCD classification typology) at 30-meter spatial resolution on an annual time step for the years 1985-2023 for the conterminous United States. Research is underway to improve the methodology for producing and validating land cover and change related components included in the next-generation product suite and follow-on products. The results will provide USGS with leading-edge capabilities for land cover monitoring, assessments, and projections.

In the coming months, USGS in collaboration with the MRLC, will publish a 2021 CONUS land cover suite (NLCD 2021). Later in 2023, we will release the Conterminous United States (CONUS) Reference Data product updated through 2021, followed by a validation assessment of the Collection 1.3 LCMAP CONUS Science Products. After Collection 1.3, no further production of LCMAP Science Products will occur.

Land cover refers to the classification of surface cover on the ground, whether forest, urban infrastructure, bodies of water or agricultural land, etc., helping to distinguish natural and anthropogenic features. Identifying, delineating, and mapping land cover (or land use) is important for global, regional and local monitoring studies, resource management and planning activities. Land cover classes can include natural features such as tropical forest, shrubland, grassland, and water bodies, but also human-made features such as urban areas and cropland.

This new land cover map, presented by the CEC, harmonizes land cover classification into 19 comparable classes across Canada, Mexico and the United States. The NALCMS land cover classes are based on the Land Cover Classification System (LCCS) standard developed by the Food and Agriculture Organization (FAO) of the United Nations.

Amazon RDS Multi-AZ is available for RDS for PostgreSQL, RDS for MySQL, RDS for MariaDB, RDS for SQL Server, RDS for Oracle, and RDS for Db2. Amazon RDS Multi-AZ with two readable standbys is available for RDS for PostgreSQL and RDS for MySQL. To learn how Amazon Aurora provides enhanced availability by making your data durable across three Availability Zones, see Multi-AZ deployments with Aurora Replicas.

For Single-AZ deployments, Multi-AZ deployments with one standby instance, and Multi-AZ deployments with two readable standbys, pricing is per DB instance-hour consumed, from the time a DB instance is launched until it is stopped or deleted. Partial DB instance-hours are billed in one-second increments with a 10 minute minimum charge following a billable status change such as creating, starting, or modifying the DB instance class.

Describes Amazon RDS Multi-AZ with two readable standbys concepts and provides instructions on modifying, renaming, rebooting, and deleting a cluster; using read replicas; and using PostgreSQL logical replication with Multi-AZ DB clusters.

During certain types of planned maintenance, or in the unlikely event of DB instance failure or Availability Zone failure, Amazon RDS will automatically failover to the standby so that you can resume database writes and reads as soon as the standby is promoted. Since the name record for your DB instance remains the same, your application can resume database operation without the need for manual administrative intervention. With Multi-AZ deployments, replication is transparent. You do not interact directly with the standby, and it cannot be used to serve read traffic. More information about Multi-AZ deployments is in the Amazon RDS User Guide.

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