-=Details=-There are 5 main component areas (and Network) that make up a GXL system:Processing Server(s) – The engine that drives the GXL; processing servers are responsible for handling the geo-processing requirements. Any number of processing servers can be added to ensure that throughput requirements are met. This includes adding additional servers so that the GXL’s processing throughput grows with the throughput requirements of the organization.Controller – Houses the database and webserver. The controller is also responsible handling PCI’s proprietary load-balancing capability to ensure that all processing servers are processing at maximum capacity.Client Computer – Any device with a supported web browser can access the GXL’s operator interface (JPS-Administrator) to setup, submit and monitor processing jobs.Quality Control Workstations – Geomatica is installed to ensure that all manual QA and editing can be applied in an efficient and seamless manner. Data Server – The GXL interfaces with the customer’s data server or SAN (Storage Area Network) in order to access input data and store output data.Network – a common switch (i.e. 10/100Mbps) is required between the controller and the rest of the system. However, a high speed switch (i.e. fiber) is required between the data server and processing servers.
View in Presentation Mode-=Details=-The processing servers represent the primary engines that drive the GXL system. The Processing servers are responsible for handling the geo-processing tasks submitted to the GXL. The GXL system is readily scalable; any number of additional processing servers can be easily added to meet increasing throughput demands. The processing servers are built using state-of-the-art commercial off-the-shelf (COTS) hardware, such as: Multi-core hyper-threaded processors, NVIDIA Graphical Processing Units (GPUs), high performance disk drives and more. Furthermore, PCI’s industry leading geo-processing algorithms were re-engineered for the GXL using standard architectures like OpenMP and CUDA to take advantage of multi-threaded and GPU processing, respectively. Hardware utilized by processing servers represent components which are commonly available and easy to acquire.
-=Details=-The controller is responsible for handling system requests and managing resource allocation. The controller houses the system database, web server and licensing server. PCI has developed proprietary software that allows the controller to automatically and efficiently distribute processing tasks between multiple processing servers, which is based on a load balancing methodology. This helps to ensure that processing server resources are maximized, but never overloaded. The controller is also responsible for hosting the operator interface portal, which is possible through the Apache Tomcat webserver and PostgreSQL database.Hardware utilized by controller represents components which are commonly available and easy to acquire.
-=Details=-One of the advantages of the GXL is that it does not require that any client software be installed. GXL operators can access the operator interface (JPS Administrator) through any supported web browser on any workstation that has network access to the GXL’s web server. Depending on how the GXL is deployed, users may be restricted to computers on the local area network (LAN) or through any computer connected to the internet (WAN). The GXL’s operator interface (JPS Administrator) is where users can submit and actively monitor processing jobs. Multiple users can connect to the JPS Administrator at anytime. All hardware required by client computers comprises commonly available components which are easy to acquire.
View in Presentation Mode-=Details=-Geomatica 2012 is installed on the quality control workstations, which allows users to manually check the quality of the outputs and perform any and all required corrections. Common operations include: Ground Control Point (GCP) editing, Tie Point (TP) editing, DEM editing, cut-line editing and color balancing. Geomatica 2012 includes an application called Mosaic Tool, which has been specifically engineered to work seamlessly with the GXL and is well integrated into the workflow. For example, the output from the mosaic preparation stage is a lower resolution mosaic with all cut-lines generated and color balancing applied. This output can be directly loaded into Geomatica’s Mosaic Tool for quality control and manual editing. The hardware comprising the quality control workstations required to QA data products produced by the GXL are commonly available and easy to acquire.
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-=Details=-The data servers or SAN are not delivered with the GXL, but rather interface to the GXL so that the GXL system can pull input data required for processing and conversely, store output data upon completion. The GXL never modifies the input data directly, which eliminates the chance of the GXL corrupting input data.
View in Presentation Mode-=Details=-The user would log into the system using the web-based operator interface, named the JPS Administrator, which can be accessed from any supported web-browser, such as, Mozilla’s Firefox or Microsoft’s Internet Explorer. Once the user has accessed the JPS Administrator, they can setup and submit processing jobs, which include, automated end-to-end batch workflows or separate processing modules (Functions). Once the user submits a processing request, the information is sent to the controller and stored in the system’s database. The controller is then responsible for identifying a processing server or servers with available processing resources. If there are no processing resources available (i.e. other processing jobs are running), then the controller will queue the submitted processing request until resources from one of the servers becomes available. As soon as enough processing resources become available on one or more of the processing servers, the controller will begin distributing the submitted job to the servers for processing. Once a job is submitted to the processing server, the server will then copy the data from the data server(s) over the network. A local copy of the data is saved on the processing server so that the raw data is never written to, which eliminates the possibility of data corruption occurring on the original input dataset. Once the processing has finished, the server will copy the output file to the output directory on the data server and delete all temporary files (inputs and derived). The processing server will also inform the controller that processing resources are available and that another queued processing job can be sent to the server. The system also includes an email notification tool that will automatically email the user with processing updates when milestones are met or when the status of a processing job changes.
-=Details=-By moving to the GPU-based architecture (employing nVidia GPUs), the GXL software has gained remarkable speed and performance boosts. CUDA is a proprietary architecture developed by NVIDIA, which is used for sending processes to NVIDIA`s Graphical Processing Units (GPUs). The CUDA architecture is a widely accepted architecture standard for graphical processing and is optimized specifically for NVIDIA GPU products. GPUs and CUDA are uniquely suited to complex mathematical computations with greater speed and precision than traditional CPUs.PCI Geomatics is the leader in the geospatial software industry in utilizing GPU technology to process large quantities of geospatial data faster and more accurately than any other geospatial software vendor.
-=Details=-One of the primary benefits of using a GPU instead of a CPU occurs for highly parallelizable operations. The processing on a single GPU core is slower than that on a single CPU core. However, a GPU contains hundreds of small processing cores (See figure above) that are capable of performing many concurrent processes, which can significantly decrease the net processing time of certain algorithms.
-=Details=-All GXL functions have been re-engineered so that parallel processing is possible. Parallel processing allows independent operations in an algorithm (function) to be processed concurrently. This allows the GXL to take advantage of multiple cores and threads on a given processing server.
-=Details=-The algorithms in the GXL have been developed using the OpenMP API, which is designed to support advanced parallel processing between CPU cores and threads. The OpenMP standard is an open source standard that has been widely adopted in the IT sector. OpenMP standards are developed by a large IT community, but official standards are approved and released by ARB, which is a not-for-profit corporation that owns OpenMP.
View in Presentation Mode-=Details=-Multiple processing nodes (servers) are connected together to handle processing in a distributed manner. GXL Satellite features a flexible, scalable architecture that can be expanded with additional processing nodes to handle increased throughput. High-volume ortho-mosaic throughput (1000+ images per day) can easily be achieved through a GXL system that can be tailored to different operational requirements.
JPSAdmin – Web Interface:DetailsThis slide illustrates that the GXL Aerial can be accessed by operator’s from any computer or device over the internet. The device must contain a valid web browser. The purpose of this slide is to not only communicate that the GXL Aerial is operated using a web-based client, but more importantly, why a web interface was chosen and what the main benefits are for accessing the GXL’s operator interface over the web as oppose to a desktop client. Key Points:Access locally over your LAN from any computer on your office network (Most secure)No installation software required when adding additional operatorsThe processing servers are on a dedicated machine (server), which is separate from the operators’ computers, ensuring that resources are free on the operators’ computers (to do other tasks), as the intensive processing takes place on the processing serversAccess from anywhere in the world (WAN). This is valuable for operators that travel for business or run processes overnight or on weekends. For the former, the operator can submit jobs, monitor progress and troubleshoot while off campus. For the latter, the operator no longer has to come into the office after-hours, especially on weekends to check progress, troubleshoot or begin a new process. Furthermore, automatic email service will be coming soon, which means that the operator will automatically be emailed when a job finishes or if a job fails. This allows the operator to focus on their current task, whether it is spending time with the family on weekends or supporting a customer off-campus (Less secure)
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Times vary with projects due to several factors, for instance image-size, overlap (affects colour balance and cutline calculations) and channels.
