What's New in Intel Array Visualizer 15? Features, Benefits, and Tips

FPGAs contain an array of programmable logic blocks, and a hierarchy of reconfigurable interconnects allowing blocks to be wired together. Logic blocks can be configured to perform complex combinational functions, or act as simple logic gates like AND and XOR. In most FPGAs, logic blocks also include memory elements, which may be simple flip-flops or more complete blocks of memory.[1] Many FPGAs can be reprogrammed to implement different logic functions, allowing flexible reconfigurable computing as performed in computer software.

Intel array visualizer 15

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Some FPGAs have analog features in addition to digital functions. The most common analog feature is a programmable slew rate on each output pin, allowing the engineer to set low rates on lightly loaded pins that would otherwise ring or couple unacceptably, and to set higher rates on heavily loaded high-speed channels that would otherwise run too slowly.[19][20] Also common are quartz-crystal oscillator driver circuitry, on-chip resistance-capacitance oscillators, and phase-locked loops with embedded voltage-controlled oscillators used for clock generation and management as well as for high-speed serializer-deserializer (SERDES) transmit clocks and receiver clock recovery. Fairly common are differential comparators on input pins designed to be connected to differential signaling channels. A few mixed signal FPGAs have integrated peripheral analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) with analog signal conditioning blocks allowing them to operate as a system-on-a-chip (SoC).[21] Such devices blur the line between an FPGA, which carries digital ones and zeros on its internal programmable interconnect fabric, and field-programmable analog array (FPAA), which carries analog values on its internal programmable interconnect fabric.

The most common FPGA architecture consists of an array of logic blocks called configurable logic blocks (CLBs), or logic array blocks (LABs), depending on vendor, I/O pads, and routing channels.[1] Generally, all the routing channels have the same width (number of signals). Multiple I/O pads may fit into the height of one row or the width of one column in the array.

"An application circuit must be mapped into an FPGA with adequate resources. While the number of logic blocks and I/Os required is easily determined from the design, the number of routing channels needed may vary considerably even among designs with the same amount of logic. For example, a crossbar switch requires much more routing than a systolic array with the same gate count. Since unused routing channels increase the cost (and decrease the performance) of the FPGA without providing any benefit, FPGA manufacturers try to provide just enough channels so that most designs that will fit in terms of lookup tables (LUTs) and I/Os can be routed. This is determined by estimates such as those derived from Rent's rule or by experiments with existing designs."[22]

To simplify the design of complex systems in FPGAs, there exist libraries of predefined complex functions and circuits that have been tested and optimized to speed up the design process. These predefined circuits are commonly called intellectual property (IP) cores, and are available from FPGA vendors and third-party IP suppliers. They are rarely free, and typically released under proprietary licenses. Other predefined circuits are available from developer communities such as OpenCores (typically released under free and open source licenses such as the GPL, BSD or similar license), and other sources. Such designs are known as "open-source hardware."

The primary differences between complex programmable logic devices (CPLDs) and FPGAs are architectural. A CPLD has a comparatively restrictive structure consisting of one or more programmable sum-of-products logic arrays feeding a relatively small number of clocked registers. As a result, CPLDs are less flexible, but have the advantage of more predictable timing delays and a higher logic-to-interconnect ratio.[citation needed] FPGA architectures, on the other hand, are dominated by interconnect. This makes them far more flexible (in terms of the range of designs that are practical for implementation on them) but also far more complex to design for, or at least requiring more complex electronic design automation (EDA) software. In practice, the distinction between FPGAs and CPLDs is often one of size as FPGAs are usually much larger in terms of resources than CPLDs. Typically only FPGAs contain more complex embedded functions such as adders, multipliers, memory, and serializer/deserializers. Another common distinction is that CPLDs contain embedded flash memory to store their configuration while FPGAs usually require external non-volatile memory (but not always). When a design requires simple instant-on (logic is already configured at power-up) CPLDs are generally preferred. For most other applications FPGAs are generally preferred. Sometimes both CPLDs and FPGAs are used in a single system design. In those designs, CPLDs generally perform glue logic functions, and are responsible for "booting" the FPGA as well as controlling reset and boot sequence of the complete circuit board. Therefore, depending on the application it may be judicious to use both FPGAs and CPLDs in a single design.[66]

To inspect the NetCDF files there are several viewers available. They are all free and all have their strengths Panoply : ncBrowse: intel array visualizer: -us/articles/intel-array-visualizer

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Awardees may file patent applications, providing that they grant to Intel a non-exclusive, worldwide, royalty-free, sub-licensable license to all intellectual property rights in any inventions or works of authorship resulting from research conducted under the joint award.

" Because of the user experience we are trying to achieve, it is important to find the perfect balance of price and performance for each of our products. Though Intel DevCloud for the Edge and its well prepared tools and environment, we were able to decrease the time it took to do a wide array of hardware tests on our interactive digital signage solutions, like Intelligent Label. "

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The components in the demo are created using a Seldon base docker image that includes a compiled OpenVINO Inference Engine with Python API and can be used to implement the code for executing the inference operations. For more details, refer to the documentation on software.intel.com or github. This base image also includes Intel Optimizations for TensorFlow with Intel Math Kernel Library (Intel MKL) and OpenCV Python packages. It can be used to improve inference performance with standard TensorFlow models and images pre/post processing.

• Other changes that may affect your application: The API now returns collections instead of arrays. We now usegenerics in the collections, so the API can return strongly-typedunmodifiable collections, without extra copies to protect of the data.In particular, this can be seen in the EntityDomain class withthe getAllAttributes(),getAllSupertypes(),getKnownSubtypes(),getLocalAttributes(), getLocalSupertypes(), and theSelectionBase.getSelections() functions.

• The Part21Writer.parse() method now throwsSTDevException. Previously it did not throw any checkedchecked exceptions.

• The TypeException class is now a subtype ofjava.lang.ClassCastException. This will allow aggregates toconform to the contract of the Java Collections Framework while stillthrowing an ST-Developer specific type conversion exception.

• The SelectTypeException class is now a subtype ofTypeException (and thus a subtype ofjava.lang.ClassCastException.

• The constructor of EntityIDTable is now private.Application code should always have been creating the table using theEntityIDTable.forModel() static method, but now this is theonly way to create the EID Table.

• The AggregateObject.getInstances() method was removed fromthe API. This was a utility method that was of dubious utility.

• The type of entity instance IDs was changed from aBigInteger to int to save memory.

• Reorganized the type hierarchy for Aggregate. Aggregates ofBINARY, BOOLEAN, LOGICAL, and STRING are now implemented as subtypesof AggregateObject. Previously, they were implemented asdirect subtypes of Aggregate. This change should not affectthe user code.

• Reorganized entity instance classes and populations. Instancesnow are actually contained in a population. This change resulted insavings of about 4-5 words per object due to the elimination of a hashtable. This change also means that we have theEntityInstance.getPopulation() method added to the API. It isno longer possible to associate a single instance with multiplemodels, as it was in previous releases.

Additional Java Library ChangesAdded line-wrapping code to the Part 21 writer. The writer willnow insert newline characters into the file to keep each line in thefile from getting too long, while insuring that a line never beginswith a dot character (to protect the Part 21 file from corruption ifit gets sent through e-mail). This change results in a similarbehavior to the C++ version of the Part 21 writer. 2ff7e9595c