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Hall-effect sensor ICs enhance ADAS safety

Wed, Mar 27, 2019

Two Hall-effect sensor ICs have been announced by Allegro Microsystems for systems that require functional safety.

The APS11450 is a family of unipolar switch ICs and the APS12450 devices are bipolar latches. They are pin-compatible upgrades for existing three-wire Hall switch and latch ICs developed in accordance with ISO 26262:2011 with ASIL-B capability (pending assessment).

The magnetic sensors have integrated self-test features that are always active in the background while the system is running. This leads to very short fault detection times, says Allegro. The action is automatic, and the tests are executed, typically in 25 micro seconds, making them transparent to the host system. Allegro points out this is even in latches used in high-speed motors and encoders. The voltage-mode output communicates the sensor’s status (including the safe state), while remaining backward compatible with logic-level interfaces, application circuits, wiring, and firmware.

The APS11450 and APS12450 are designed to enhance automotive applications and intelligent motion systems, such as advanced driver assistance systems (ADAS) and encoders for windows, seat motors, seatbelt tensioners, and closure systems. The ICs are also suited for off-road vehicles, heavy equipment, human machine interfaces (HMI) and roll-over (bank angle) sensors, kickstands and driver controls in two-wheeled vehicles.

The APS11450 and APS12450 are qualified beyond the requirements of AEC-Q100 grade 0, says Allegro. They were developed to ISO 26262 as a hardware safety element with ASIL-B capability (pending assessment) for automotive safety systems.

When using the APS11450 or APS12450 devices, developers can achieve an ASIL-B (or higher) rating without redundant sensors, for smaller, less expensive systems.

Two package choices are available, with magnetic characteristics that match legacy Hall sensors. The monolithic ICs operate from 3.3 to 24V and at up to 175 degrees C junction temperature, surviving up to +35V inputs, reverse-battery (-30V), output shorts, load-dump, and other over-voltage transients. Allegro’s miniature LH package is a SOT-23W style package for surface mount applications and the UA version is a three-pin, single inline package (SIP) for through-hole mounting. Both packages are lead (Pb) -free, with 100 per cent matt-tin leadframe plating.

http://www.allegromicro.com

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Infineon claims industry’s first true 1000A voltage regulator for AI

Tue, Mar 26, 2019

Adding to its high current system chipset portfolio, Infineon claims to offer the industry’s first 16-phase digital PWM multiphase controller.

The XDPE132G5C extends the existing portfolio which enables currents of 500 to 1000A and above for next generation CPUs, GPUs, FPGA and ASICs used in artificial intelligence (AI) and 5G datacomms applications.

It has been introduced as CPU current requirements increase to enable next-generation AI and networking workloads, DC/DC voltage regulators to deliver more than 500A to the load. The XDPE132G5C has a true 16-phase digital PWM engine and an improved advanced transient algorithm to address these high phase count requirements, says Infineon. The true active current sharing between phases enables a reliable, compact and cost-saving design, with no need for extra logic doubler ICs.

The XDPE132G5C offers fine V out setting in 0.625mV increments to meet the demands of ASICs and FPGAs of V out control in less than 1mV steps, seen in communication systems today. The XDPE132G5C also supports auto-restart for communications with options to reduce remote site maintenance following power or system glitches.

The XDPE132G5C is packaged in a 7.0 x 7.0mm 56-pin QFN to accommodate 16 phases. It employs a full digital and programmable load line and is PMBus 1.3/AVS-compliant.

Infineon advises that it can be paired with TDA21475, the thermally efficient integrated current sense power stage, to efficiently deliver over 1000A.

The 70A-rated TDA21475 power stage is housed in a 5.0 x 6.0mm package. It provides efficiency of more than 95 per cent. The exposed top significantly reduces the R th(j-top) from 19 degrees C/W in the over-moulded package to 1.6 degrees C/W. This removes heat from the top of the package, for voltage regulator power density and optimal phase count and footprint. The TDA21475 also offers smart over-current and over-voltage protection and delivers temperature and current information to the XDPE132G5C controller.

The company also offers the IR35223 true 10-phase PWM digital controller. This controller provides a cost-effective option for voltage regulation up to 500 A. The IR35223 is housed in a 6.0 x 6.0mm, 48-pin QFN package and provides advanced transient performance and telemetry features including PMBus 1.3/AVS bus compliance.

http://www.infineon.com/next-gen-processors

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ML inference software library makes CNNs power-efficient

Tue, Mar 26, 2019

Machine learning (ML) inference software from Synopsys is optimised for low power IoT applications that use convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

The embARC Machine Learning Inference (MLI) software library supports the energy-efficient Synopsys DesignWare ARC EM DSP and HS DSP processors. It is claimed to boost performance up to 16X for 2D convolution layers compared to unoptimised implementations and accelerates RNNs up to a factor of five for a range of topologies, including those built with long short-term memory (LSTM) cells.

The embARC Machine Learning Inference software library is designed to help developers create power-efficient neural network system on chip (SoC) designs incorporating Synopsys’ DesignWare ARC EM and HS DSP processor IP. The software library provides developers with optimised functions to implement neural network layer types, significantly reducing processor cycle counts for applications that require low power and area, such as voice detection, speech recognition, and sensor data processing, says Synopsys.

The embARC MLI software library is available through embARC.org, a dedicated website that provides software developers access to free and open source software, drivers, operating systems, and middleware supporting ARC processors.

The embARC MLI software library supports ARC EMxD and HS4xD processors and provides a set of kernels for effective inference of small- or mid-sized machine learning models. It enables the efficient implementation of operations such as convolutions, long short-term memory (LSTM) cells, pooling, activation functions such as rectified linear units (ReLU), and data routing operations, including padding, transposing, and concatenation, while reducing power and memory footprint.

Synopsys cites the example of low-power neural network benchmarks such as CIFAR-10 running on an ARC EM9D processor which can achieve up to a four fold reduction in cycle count compared to competitive processors in the same class, claims Synopsys. The MLI library provides an average of three to five times performance improvement across a wide range of neural network layers, such as depth-wise 2D convolution, fully connected, basic RNN cells, and LSTM cells with a maximum performance boost of up to 16X for 2D convolution layers.

Picture credit: iStock

https://www.synopsys.com

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Infineon claims industry’s first true 1000A voltage regulator for AI

Tue, Mar 26, 2019