UI scientists create powerful microbatteries

UI …. i.e. University of Illinois…

Developed by researchers at the University of Illinois at Urbana-Champaign, the new microbatteries out-power even the best supercapacitors and could drive new applications in radio communications and compact electronics.

The most powerful batteries on the planet are only a few millimeters in size, yet they pack such a punch that a driver could use a cellphone powered by these batteries to jump-start a dead car battery – and then recharge the phone in the blink of an eye.

“This is a whole new way to think about batteries. A battery can deliver far more power than anybody ever thought. In recent decades, electronics have gotten small. The thinking parts of computers have gotten small. And the battery has lagged far behind. This is a microtechnology that could change all of that. Now the power source is as high-performance as the rest of it,” said William P. King, bliss professor of mechanical science and engineering.

^{“The picture illustrates a high power battery technology from the University of Illinois.  Ions flow between three-dimensional micro-electrodes in a lithium ion battery.”}

With currently available power sources, users have had to choose between power and energy. For applications that need a lot of power, like broadcasting a radio signal over a long distance, capacitors can release energy very quickly but can only store a small amount. For applications that need a lot of energy, like playing a radio for a long time, fuel cells and batteries can hold a lot of energy but release it or recharge slowly.

The new microbatteries offer both power and energy, and by tweaking the structure a bit, the researchers can tune them over a wide range on the power-versus-energy scale.

The batteries owe their high performance to their internal three-dimensional microstructure. Batteries have two key components: the anode (minus side) and cathode (plus side). Building on a novel fast-charging cathode design by materials science and engineering professor Paul Braun’s group, King and Pikul developed a matching anode and then developed a new way to integrate the two components at the microscale to make a complete battery with superior performance.

The graphic illustrates a high power battery technology from the University of Illinois.  Ions flow between three-dimensional micro-electrodes in a lithium ion battery.

With so much power, the batteries could enable sensors or radio signals that broadcast 30 times farther, or devices 30 times smaller. The batteries are rechargeable and can charge 1000 times faster than competing technologies – imagine juicing up a credit-card-thin phone in less than a second. In addition to consumer electronics, medical devices, lasers, sensors and other applications could see leaps forward in technology with such power sources available.

“Any kind of electronic device is limited by the size of the battery – until now. Consider personal medical devices and implants, where the battery is an enormous brick, and it’s connected to itty-bitty electronics and tiny wires. Now the battery is also tiny,” explained Mr. King.

Now, the researchers are working on integrating their batteries with other electronics components, as well as manufacturability at low cost.

“To dare is to lose one's footing momentarily. To not dare is to lose oneself.”

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Xilinx enables C programmable FPGAs

The Vivado Design Suite 2013.1 includes a new IP-centric design environment designed to accelerate system integration, and a set of libraries to accelerate C/C++ system-level design and high-level synthesis (HLS). The update provides a workflow that does not dictate how a design team works.

Users of Vivado HLS can access video processing functions integrated into an OpenCV environment for embedded vision running on the dual-core ARM processing system.

It delivers, says Xilinx, up to a 100X performance improvement of existing C/C++ algorithms through hardware acceleration.

Read more…

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India needs homegrown wafer fabs for its electronics

The government of India is offering up to $2.75 billion in incentives for the construction and equipping of the country's first wafer fabrication facility. India imported $8.2 billion in semiconductors last year, according to Gartner. Getting its own wafer fab is said to present a number of challenges to India, especially in the necessary infrastructure and an ecosystem of suppliers.

The domestic purchasing mandate, known as the “preferential market access” policy, seeks to address a real problem: imports of electronics are growing so fast that by 2020, they are projected to eclipse oil as the developing country’s largest import expense.

India’s import bill for semiconductors alone was $8.2 billion in 2012, according to Gartner, a research firm. And demand is growing at around 20 percent a year, according to the Department of Electronics and Information Technology.

For all electronics, India’s foreign currency bill is projected to grow from around $70 billion in 2012 to $300 billion by 2020, according to a government task force.

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20nm 32-Gbps transceiver from Altera

Altera has announced the successfull demonstration of a programmable device, with 32-Gbps transceiver capabilities, based on TSMC's 20SoC process technology.

The company states that this validates the performance capabilities of 20nm silicon and is a positive indicator for next-generation devices in performance demanding, bandwidth-centric applications.

“Today’s news represents a significant milestone for the industry and for the transceiver development team at Altera,” said Vince Hu, vice president of product and corporate marketing at Altera.

“These 20 nm devices contain the key IP components that will be included in our next-generation FPGAs and validating them now provides us confidence we will deliver to the market 20 nm FPGAs on schedule.”

For more information, see www.altera.com/32gbps-20nm

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Transition Delay and Propagation Delay

Transition delay or slew is defined as the time taken by signal to rise from 10 %( 20%) to the 90 %( 80%) of its maximum value. This is known as “rise time”.

Similarly “fall time” can be defined as the time taken by a signal to fall from 90 %( 80%) to the 10 %( 20%) of its maximum value.

Transition is the time it takes for the pin to change state.

Setting Transition Time Constraints

The above theoretical definitions are to be applied on practical designs. Now, the transition time of a net becomes the time required for its driving pin to change logic values (from 10 %( 20%) to the 90 %( 80%) of its maximum value). This transition time used foe delay calculations are based on the timing library (.lib files).

Transition related constraints can be provided in Design Compiler (logic synthesis tool from Synopsys) by using below commands:

1. max_transition : This attribute is applied to each output of a cell. During optimization, Design Compiler tries to make the transition time of each net less than the value of the max_transition attribute.

2. set_max_transition: This command is used to change the maximum transition time restriction specified in a technology library.

“This command sets a maximum transition time for the nets attached to the identified ports or to all the nets in a design by setting themax_transition attribute on the named objects.

For example, to set a maximum transition time of 3.2 on all nets in the design adder, enter the following command:

         set_max_transition 3.2 [get_designs adder]

To undo a set_max_transition command, use the remove_attributecommand. For example, enter the following command:

         remove_attribute [get_designs adder] max_transition”

(Directly quoted from Design Complier user manual)

Setting Capacitance Constraints

The transition time constraints specified above do not provide a direct way to control the actual capacitance of nets. To control capacitance directly, below command has to be used:

set_max_capacitance: This command sets the maximum capacitance constraint on input ports or designs.

In addition to set_max_transition, set_max_capacitance can also be used as this command works independent.

This command applies maximum capacitance limit to output pin or port of the design.

This command can also be used to apply capacitance limit on any net.
Eg:
         set_max_capacitance 4 [get_designs decoder]

To remove the set_max_capacitance command, use theremove_attribute command.

           remove_attribute [get_designs decoder] max_capacitance

 

Propagation Delay

Propagation delay is the time required for a signal to propagate through a gate or net.

Hence if it is cell, you can call it as “Gate or Cell Delay” or if it is net you can call it as “Net Delay”

Propagation delay of a gate or cell is the time it takes for a signal at the input pin to affect the output signal at output pin.

For any gate propagation delay is measured between 50% of input transition to the corresponding 50% of output transition.

There are 4 possibilities:

Propagation delay between 50 % of Input rising to 50 % of output rising.

Propagation delay between 50 % of Input rising to 50 % of output falling.

Propagation delay between 50 % of Input falling to 50 % of output rising.

Propagation delay between 50 % of Input falling to 50 % of output falling.

Each of these delays has different values. Maximum and minimum values of these set are very important. Maximum and minimum propagation delay values are considered for timing analysis.

For net propagation delay is the delay between the time a signal is first applied to the net and the time it reaches other devices connected to that net.

Propagation delay is taken as the average of rise time and fall time i.e. Tpd= (Tphl+Tplh)/2.

Propagation delay depends on the input transition time (slew rate) and the output load. Hence two dimensional look up tables are used to calculate these delays. How to calculate propagation delay of net and gate? Please refer below articles to find the detailed explanation.

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Use SystemVerilog for coverage metrics

The design-and-verification industry is at the intersection of two important trends in the design and verification of SOC (system-on-chip) devices: the adoption of SystemVerilog HDVL (hardware-description and -verification language) and the increasingly critical role for coverage metrics. The interest in System Verilog is understandable; this IEEE-standard language has the features for RTL (register-transfer-level) design, high-level modeling, testbench creation, and assertion specification (Reference).

SystemVerilog also provides constructs for design-and-verification engineers to specify functional coverage points—conditions that designers must exercise for complete verification of the design. Designers increasingly use functional coverage to supplement traditional code coverage. The primary driver for this evolution is the widespread use of constrained-random-stimulus generation.

Traditional verification plans typically include a list of design features or tests that verify features and test status. This approach has worked well with handwritten, directed tests because of the clear correspondence between features and tests. However, verification consists of writing and running each test in simulation, perhaps after turning on some code coverage to help identify features you may have missed in the plan.

Constrained-random-stimulus generation requires a different approach, in which each automatically generated test can exercise many features and parts of the design. A modern verification plan lists features, functional coverage points for the features, and coverage status. You gauge verification closure by the number of coverage points you exercise rather than the number of tests you complete.

SystemVerilog provides all the features necessary to develop both handwritten tests and constrained-random testbenches and to track progress toward closure. Most simulators have built-in code coverage for the new design constructs that SystemVerilog introduces. Thus, code-coverage metrics are available for designs taking advantage of the language's advanced RTL features.

SystemVerilog provides several powerful specification methods for functional coverage. The first is cover property, which is part of the SVA (SystemVerilog Assertions) subset of the language. SVA's assertion features, including temporal sequences, are also available for functional coverage.
For example,

MiniMuM and MaxiMuM response
minimum_response: cover property (@(posedge clk)
(req ##1 ack ));
maximum_response: cover property (@(posedge clk)
(req ##5 ack ));

Above example ensures that the simulator exercises the two extremes—one and five cycles—of a request-acknowledge handshake. Both simulators and many formal-analysis tools support the cover-property construct. If formal analysis can prove that a coverage point is unreachable, a design bug may be blocking important functions from being exercised. If formal analysis instead provides a trace showing how to reach a coverage point, this trace can provide a good hint on how to write or generate a test.

Beyond individual coverage properties, you sometimes must track ranges of values. SystemVerilog provides the cover-group construct, which is not part of SVA, to perform this function.
For example,

PayLoad sizes of incoming Packets
minimum_response: cover property (@(posedge clk)
(req ##1 ack ));
maximum_response: cover property (@(posedge clk)
(req ##5 ack ));
covergroup payloads_seen (@(packet_received);
coverpoint payload_size {
bins empty = { 0 };
bins minimum = { 1 };
bins maximum= { 1023 };
bins others = default; }
endgroup : payloads_seen

Above example tracks the payload sizes of incoming packets on a network interface and ensures the coverage of corner cases of empty, minimum, and maximum payloads. SystemVerilog also provides the cross construct to measure cross-coverage between two coverage points. This feature allows the tracking of combinations of coverage metrics.
For example,

EnumEratEd typE for four packEt cLassEs

enum { read, write, atomic, ctrl } packet_class;
covergroup packets_seen (@(packet_received);
coverpoint payload_size {
bins empty = { 0 };
bins minimum = { 1 };
bins maximum= { 1023 };
bins others = default; }
coverpoint packet_class;
cross payload_size, packet_class;
endgroup : packets_seen

Above example specifies an enumerated type for four packet classes for the network interface, adds a cover point to track the packet classes, and crosses the packet types with the payload sizes.

Ultimately, the SOC-tapeout decision must take into account all coverage metrics. Although functional coverage is the primary method, code coverage has value as a backup to identify areas of the design with no functional coverage due to an incomplete verification plan. The project team needs to merge together code- and functional-coverage results to assess verification progress and help determine verification closure. Coverage is critical for modern, constrained-random verification. Without effective metrics, no reliable way exists to gauge status and manage progress. In addition to its other features and benefits, SystemVerilog provides support for functional coverage. By including coverage in the verification plan from the start of the project and taking advantage of SystemVerilog, the SOC team can employ a complete plan-to-closure methodology that greatly increases the chances for a successful product.

3D IC market to see stable growth through 2016

The global 3D integrated circuit market is forecast to grow by 19.7 percent between 2012 and 2016, with the major growth driver being strong demand for memory products, particularly flash memory and DRAM.

3D integrated circuits help improve the performance and reliability of memory chips, and as an added benefit the resulting chips are smaller and cheaper. However, chips based on 3D circuits face thermal conductivity problems which might pose a challenge to further growth.

According to Infiniti Research, the biggest 3D IC vendors at the moment are Advanced Semiconductor Engineering (ASE), Samsung., STMicroelectronics and Taiwan Semiconductor Manufacturing Co. (TSMC). IBM, Elpida, Intel and Micron are also working on products based on 3D ICs.

Intel was a 3D IC pioneer and it demoed a 3D version of the Pentium 4 back in 2004. The overly complicated chip offered slight performance and efficiency improvements over the 2D version of the chip, which really isn't saying much since Prescott-based Pentium 4s were rubbish.

The focus then shifted on memory chips and some academic implementations of 3D processors, but progress has been relatively slow, hence any growth is more than welcome.