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PIK EDF 100/60S_Datasheet PDF

时间:2021-06-14 00:56:09 来源:网络整理编辑:JAE Electronics

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The combination sensor is actually smaller than the fingerprint-only sensor. A small sliver of silicon was added to the capacitive fingerprint sensor die for a small array of light sensors. The die cost increases minimally. The more significant cost added for the combination sensor is an external LED and the cost of adding light windows in the package for the LED light to escape and the reflected light to enter.

The combination sensor is actually smaller than the fingerprint-only sensor. A small sliver of silicon was added to the capacitive fingerprint sensor die for a small array of light sensors. The die cost increases minimally. The more significant cost added for the combination sensor is an external LED and the cost of adding light windows in the package for the LED light to escape and the reflected light to enter.

What helps us is that no one customer accounts for more than a few percent of our total revenues, and last year we had a total of 24,000 different customers.”

Advances in very deep-submicron process technology require corresponding investments in design and test. Design infrastructure enabling the achievements of advanced design capability is well understood, yet the investment in test is often overlooked. With increasing device complexity and performance requirements, the big-iron” test approach requires ever-more-expensive, high-performance testers. These testers, at over $3.5 million apiece for a 512-pin, 400-MHz version, represent a large and significant contribution to the overall cost of a chip. For this capital outlay, integrated-circuit manufacturers can expect a level of capability and functionality that permits higher-frequency application of signals for broad functional test coverage, but in many cases at lower than the needed operating frequency of the device application. Yet, even with these large expenditures in testers the gap between tester frequency and device capability is widening.

PIK EDF 100/60S_Datasheet PDF

With the number of complex, multimillion-gate design starts expected to increase rapidly to greater than 4,000 in the next two to three years, IC design houses and IC manufacturing companies are forced to identify alternative methods to manage the increasingly large costs of test.

Embedded test can help mitigate the need for more complex testers. With embedded test, designers are able to include with their design embedded functions that permit on-chip, at-speed structural test of their silicon devices. These tests-initiated, controlled and evaluated on-chip-provide an internal test mechanism, which reduces the need to scale the big-iron testers to the growth curve of silicon device technology.

Embedded test enables the use of lower-performance testers to provide test coverage at or beyond that expected from the higher-cost testers. In fact, testing a 2 million-plus-gate system-on-chip (SoC) device incorporating a minimum-pin, embedded-test approach at greater than 800 MHz on a $500,000, low-performance tester would yield test coverage comparable to the high-performance tester, but deliver a capital-cost savings advantage of greater than $3 million.

PIK EDF 100/60S_Datasheet PDF

Built-in self-test (BIST)-based products that test memory and logic dominate among embedded-test technologies providing at-speed structural test. Competing approaches to embedded test include scan/automatic test-pattern generation tools that can test at speed.

Embedded test products and ATPG-based products both provide structural test capabilities initiated through an IEEE-1149.1 port. But implementation and usage differences exist with those different approaches. Scan/ATPG products require scan-memory resources resident on the tester to store stimulus and captured data. Their embedded test, BIST-based counterparts have their pattern-generation and comparison functions embedded in the silicon device itself, reducing the feature requirements of the tester.

PIK EDF 100/60S_Datasheet PDF

SoC complicates scan Memory test capability becomes a significant differentiator as the number of complex, embedded intellectual-property (IP) blocks grows on the silicon devices. Embedded test products, utilizing BIST techniques, can be made to easily scale with hierarchy and complexity with minimal (if any) impact to tester resource requirements. The SCAN/ATPG approach is challenged by increasing complexity and requires significant upgrades to tester resources to accommodate the increase in scan chains and the scan chain depth as the degree of complexity of SoC devices continues to scale.

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We also saw a push for new form factors at the show, and future flexible screens. Raj Partheban, founder of WITGrip, a startup developing IP for wrist-worn wearable technology, said smartphones do not provide the disruptive technology needed to enable intuitive and prolonged interaction with smart” homes and cities.

Manufacturers have focused on sustaining technologies, for example developing the existing smartphone so that it can control elements within the home. However, this means that phones have simply become a more sophisticated remote control — they’ve not displaced the existing solution,” Partheban said.

The company says that while the technology exists to facilitate many activities within a smart home, from contactless entry to controlling lights and heating, interaction is currently limited as although the device is connected, the user is not.  Current smartphone technologies present some of the same issues as remote-control solutions.

Adi Chhabra, a senior product manager for AI at Vodafone, also said the future of wearables is moving away from screen interactions to surface interactions. Any screen or surface can be your interface, which can be voice-enabled, touch enabled, or gesture-enabled. Google Glass was the first generation, but it wasn’t the answer for wearables. However, it’s giving us a sense of where we will be in 15 years,” he said.

Wearables were touted in the early days as smart watches and fitness trackers. But as the multiple use-cases evolve, some of the killer applications are becoming clearer. It’s currently trending towards health applications, not just in the fitness tracker sense, but in more sophisticated healthcare, as we have seen above.