1. Inflation in nearly half of major states outgrows India's Oct CPI; price pressure steepest in Chhattisgarh  Moneycontrol
2. Retail inflation surges to a 14-month high of 6.2% in October  The Times of India
3. If we exclude vegetable prices, CPI inflation remains in RBI's range: UBI research  The Economic Times
4. Rising food prices are likely to push back beginning of rate cutting cycle  The Indian Express
5. India confident of reaching USD 100 billion trade volume with Russia ahead of 2030 timeline: S Jaishankar  Telegraph India

1. Telangana train accident: Goods train derails near Peddapalli. Check full list of cancelled, diverted trains today | Today News  Mint
2. Goods train derails in Telangana's Peddapalli; 20 trains cancelled, 10 diverted  The Economic Times
3. 11 coaches of goods train derail in Telangana  The Times of India
4. Goods train derailment in Telangana affects rail traffic between Delhi and Chennai  Telangana Today
5. Goods train derails in Telangana's Peddapalli; 30 trains cancelled, several diverted  The Hindu

1. BREAKING| 'Bulldozer Reminds Of Lawlessness' : Supreme Court Says Properties Can't Be Demolished Merely...  Live Law - Indian Legal News
2. "Officials To Pay From Salary": Top Court Guidelines On 'Bulldozer Justice'  NDTV
3. ‘Heavens won’t fall on authorities if they hold their hands for some period’: SC sets pan India guidelines against bulldozer action  The Financial Express
4. Executive Can't Become Judge, Pronounce Guilt Of Persons & Punish Them By Demolishing Their Properties :...  Live Law - Indian Legal News
5. ‘Officials will pay for demolitions from their salary’: 5 Key SC observations on ‘chilling’ side of ‘bulldozer justice’  Mint

According to the latest rumors, the Samsung Galaxy Z Flip FE could be powered by the Exynos 2400 chipset which is surprising.

The post Samsung Galaxy Z Flip FE chipset of choice could surprise you appeared first on Phandroid.

Here are the best foldable smartphones you can buy in 2024.

The post Best Foldable Smartphones of 2024 appeared first on Phandroid.

In a unique online romance scam, a man in Tianjin, China, fell victim to a bizarre "marriage bed burning" ritual, costing him Rs 11 lakh.

Positioned near the side of her head, the eye provides an expansive field of vision, while a thick layer of protective blubber shields it from harm and maintains warmth.

US-based comedian Austin Nasso is going viral online for his hilarious impersonation of US-President-elect Donald Trump during a fictional visit to India.

Wind River, an IoT and industrial operating system owned by Intel will be acquired by TPG, global alternative asset firm. Terms of the deal were not disclosed. Intel had bought Wind River Systems for $884 million in 2009

Wind River operates in several markets, including aerospace and defense, automotive, industrial, medical and networking technologies. Its core products in these markets are operating systems, software infrastructure platforms, device management, and simulation software. The IoT practice of Wind River provides consulting services for customers building IoT applications.

In a statement for Wind River, Nehal Raj, Partner and Head of Technology investing at TPG said “We see a tremendous market opportunity in industrial software driven by the convergence of the Internet of Things (IoT), intelligent devices and edge computing. As a market leader with a strong product portfolio, Wind River is well positioned to benefit from these trends. We are excited about the prospects for Wind River as an independent company, and plan to build on its strong foundation with investments in both organic and inorganic growth.”

Wind River’s main IoT product is Helix Device Cloud, a cloud-offering capable of managing deployed IoT devices and industrial equipment across a machine’s lifecycle. Helix can connect and manage devices remotely.

Helix platform’s key uses cases are gateway management, proactive maintenance, security updates, and device provisioning.

Amber Solutions, an IoT product company that sells smart outlets, switches and circuit breakers closed Series A Preferred Stock round of financing that equals $3.3M in gross proceeds. Amber will use the funds to support the commercial development of Amber's core technologies.

One of Amber’s product is solid-state circuit interrupter (GFCI) that basically stops harmful levels of electricity from passing through a person. It operates as a safety device alerting the homeowner of electrocution incidents in real time.

Amber Solutions’ core markets are builders that prepare smart home/smart building ready infrastructure, certified electrical contractors or remodelers, and electrical manufacturers.

Other latest funding news include Owlet’s $24M Series B, Axonize’s $6M Series A round and addition of Deutsche Telekom as its strategic investor, and $30M Series B raised by Palo Alto-based Armis.

Microsoft announced it has acquired Semantic Machines, a conversational AI startup providing chatbots and AI chat apps founded in 2014 having $20.9 million in funding from investors. The acquisition will help Microsoft catch up with Amazon Alexa, though the latter is more focused on enabling consumer applications of conversational AI.

Microsoft will use Semantic Machine’s acquisition to establish a conversational AI center of excellence in Berkeley to help it innovate in natural language interfaces.

Microsoft has been stepping up its products in conversational AI. It launched the digital assistant Cortana in 2015, as well as social chatbots like XiaoIce. The latest acquisition can help Microsoft beef up its ‘enterprise AI’ offerings.

As the use of NLP (natural language processing) increases in IoT products and services, more startups are getting traction from investors and established players. In June last year, Josh.ai, avoice-controlled home automation software has raised $8M.

Followed by it was SparkCognition that raised $32.5M Series B for its NLP-based threat intelligence platform.

It appears Microsoft’s acquisition of Semantic Machines was motivated by the latter’s strong AI team. The team includes technology entrepreneur Daniel Roth who sold his previous startups Voice Signal Technologies and Shaser BioScience for $300M and $100M respectively. Other team members include Stanford AI Professor Percy Liang, developer of Google Assistant Core AI technology and former Apple chief speech scientist Larry Gillick.

Arduino’s MKR family of products got two new wireless connectivity boards added to its range of products. These include MKR WiFi 1010 and MKR NB 1500, both aimed at streamlining IoT product/service development.

Arduino’s blog notes that “the Arduino MKR WiFi 1010 is the new version of the MKR1000 with ESP32 module on board made by U-BLOX.”

MKR WiFi 1010: For prototyping of WI-FI based IoT applications

The core difference of MKR WiFi 1010 compared to MKR WiFi 1000 is that the former can be put to use in production-grade IoT apps and it has ESP32-based module manufactured by u-blox. The former enables to add 2.4GHz WiFi and Bluetooth capability to the application. Additionally, it comes with a programmable dual-processor system (an ARM processor and a dual-core Espressif IC).

MKR NB 1500: For on-field monitoring systems and remote-controlled LTE-enabled modules

The Arduino MKR NB 1500 is based on new low-power NB-IoT (narrowband IoT) standard. This makes it appropriate for IoT apps running over cellular/LTE networks.

Key use cases of this board are remote monitoring systems and remote-controlled LTE-enabled modules. It supports AT&T, T-Mobile USA, Telstra, Verizon over the Cat M1/NB1 deployed bands 2, 3, 4, 5, 8, 12, 13, 20 and 28.

Arduino also pitches this board to be used in IoT apps which used to rely on alternative IoT networks such as LoRa and Sigfox. It promises to save power compared to GSM or 3G cellular-based connections.

[SAPS] - Polokwane based Hawks Serious Commercial Crime Investigation in collaboration with National Traffic Anti-corruption Unit arrested 11 suspects between the ages of 27 and 57 for alleged fraud at various Provinces during operation "SISFIKILE".

[SAPS] - Five suspects are appearing in the Kariega Magistrate's Court today, after they were arrested and found in possession of cycads with an estimated value of R1 Million on Friday 08 November 2024.

[Afropop] Thandiswa Mazwai has lived the modern history of African music. In the early '90s, when she was still a teenager, she pioneered the emerging kwaito sound in South Africa, first with a trio called Jack-Knife, and then as the lead vocalist and composer for Bongo Maffin. Thandiswa's 2004 debut album as a solo artist, Zabalaza, went double platinum and established her as a major star. Since then, she has delved into jazz, rock, classic African pop styles, and more. Her latest release, Sankofa, is an expansive

[COSATU] The Congress of South African Trade Unions (COSATU) is deeply concerned by the Minister for Communications and Digital Technologies, Mr. S. Malatsi's sudden withdrawal of the South African Broadcasting Corporation (SABC) SOC Ltd Bill from Parliament where it was being engaged upon by the National Assembly's Portfolio Committee: Communications and Digital Technologies.

[Parliament of South Africa] Parliament, Tuesday, 12 November 2024 - The National Assembly (NA) will hold a plenary session scheduled to start at 10:00. Among the items on the agenda from 10:00 to 13:00 is the statement by the Minister of Water and Sanitation on water security in the country and a debate on 16 Days of Activism for no violence against women and children. The debate will be held under the theme, "Marking 30 years of democratic rights for women and fostering national unity to end gender-based violence".

The demand for higher-performance computing is greater than ever. Cutting-edge applications in artificial intelligence (AI), big data analytics, and databases require high-speed memory systems to handle the ever-increasing volumes and complexities of data. Advancements in cloud computing and machine virtualization are stretching the limits of current capabilities. AI applications hosted in the cloud rely on fast access and reduced latency in memory systems, which is amplified by an increasing number of CPU and GPU cores.

Introducing the DDR5 Multiplexed Rank DIMM (MRDIMM), the next-generation memory module technology designed to meet the needs of high-performance computing (HPC) and AI in cloud applications. By leveraging existing DDR5 DRAM memory devices, MRDIMM modules not only double the DRAM data rate but also maintain the RAS capabilities of the industry-proven RDIMM modules, setting a new precedent for memory module performance.

Let’s compare RDIMM and MRDIMM modules using the same DRAM parts. Today, high-speed production DDR5 RDIMM modules run at 5600Mbps. Those modules use DDR5 DRAM parts, which also run at 5600Mbps. An MRDIMM module using the same DDR5 5600Mbps DRAM parts will run at a blazing 11.2Gbps.

One key metric for best-in-class performance, low bit error rate (BER), and ease of adoption is the eye diagram. The eye diagram illustrates at-speed system margin and accurately represents DDR system quality when captured with a pseudo-random binary sequence (PRBS)-like pattern. The diagram below illustrates Cadence’s 3nm silicon write eye diagram for DDR5 MRDIMM IP running at 12.8Gbps.

Cadence 3nm DDR5 MRDIMM 12.8Gbps test chip write eye diagram, design kit is available today

The eye diagram is captured using a PRBS-like pattern, incorporating a package and system board representative of a typical MRDIMM channel. Using PRBS-like patterns is crucial for capturing accurate eye diagrams. Repetitive clock-like data patterns create deceptively “open eyes” that do not reflect the real system performance. Effects like intersymbol interference, simultaneous switching, reflections, and crosstalk are not accurately reflected in the eye diagrams for parallel interfaces like DDR using non-random data streams. Relying on improperly captured eye diagrams inevitably leads to a significantly worse real system BER than conveyed by that eye diagram.

Doubling the DDR5 RDIMM data rate is challenging. Achieving high performance while optimizing for area and power requires multiple design techniques. Feed-forward equalization (FFE), decision feedback equalization (DFE), continuous-time linear equalization (CTLE), and T-coils are required to reach 12.8Gbps MRDIMM data rates in multi-channel systems. Building a production-worthy 12.8Gbps DDR5 MRDIMM IP requires engineering expertise that comes from many generations of memory interface design and production experience. Cadence has developed this expertise through multiple DDR5/4, LPDDR5X/5, and GDDR6 designs in different technology nodes and foundries. For instance, Cadence’s GDDR6 IP is available in three foundries and ten process nodes, with mass production at speeds exceeding 22Gbps.

For your next project, consider DDR5 12.8Gbps MRDIMM, a technology that not only doubles the bandwidth of DDR5 RDIMM but also promises rapid proliferation into next-generation AI, data center, HPC, and enterprise applications. With its cutting-edge capabilities, the Cadence DDR5 12.8Gbps MRDIMM IP is ready to power the future of computing.

As vehicles transition into interconnected ecosystems, artificial intelligence and advanced technologies become increasingly crucial. Infotainment systems have evolved beyond mere music players to become central hubs for connectivity, entertainment, and navigation. With global demand for comfort, convenience, and safety rising, the automotive infotainment market is experiencing significant growth. Valued at USD14.99 billion in 2023, it is projected to grow at a compound annual growth rate (CAGR) of 9.9% from 2024 to 2030.

To keep pace with this evolution, infotainment systems must accommodate a range of workloads, including audio, voice, AI, and vision technologies. This requires a flexible, scalable Digital Signal Processor (DSP) solution that acts as an offload engine for the main application processor. Integrating a single DSP for varied functions offers a cost-effective solution for high-performance, low-power processing, which aligns well with the needs of Electric Vehicles (EVs).

If you missed the detailed presentation by Casey Ng, Product Marketing Director at Cadence at CadenceLIVE 2024, register at the CadenceLIVE On-Demand site to access it and other insightful presentations. Stay ahead of the curve and explore the future of innovative electronics with us.

Cadence Infotainment Solution: Leading the Charge

Cadence Tensilica HiFi DSPs play a crucial role in enhancing audio capabilities in vehicle infotainment systems. They support applications like voice recognition, hands-free calling, and deliver immersive audio experiences. This technology is also paramount for features such as active noise control, which reduces road and cabin noise, and acoustic event detection for identifying unusual sounds like broken glass. One notable innovation is the "audio bubble," enabling personalized audio zones within the vehicle, ensuring passengers enjoy distinct audio settings.

Cadence HiFi DSP technology enriches the driving experience for electric vehicles by mimicking traditional engine sounds, while its advanced audio processing ensures optimal performance across various digital radio standards. It significantly contributes to noise reduction, hence improving the cabin experience. Integrating a Double Precision Floating Point Unit (FPU) stands out, as it upgrades audio performance and Signal-to-Noise Ratio (SNR) through efficient 64-bit processing, allowing control over numerous speakers without hitches.

These advancements distinguish the DSP as an essential tool in evolving infotainment systems, offering unmatched performance and adaptability. Tensilica HiFi processors, crucial to advanced infotainment SoCs, serve as efficient offload processors, augmenting real-time execution and energy efficiency. Cadence’s ecosystem, with over 200 codecs and software partnerships, propels the evolution of innovative infotainment systems. Introducing the HiFi 5s DSP marks a new era in connected car experiences, setting the stage for groundbreaking advancements.

Exploring Tomorrow with HiFi 5s DSP Technology

The HiFi 5s represents the apex of audio and AI digital signal processing performance. Built on the Xtensa LX8 platform, it introduces capabilities like auto-vectorization, which allows standard C code to be automatically optimized for performance. This synergy of hardware and software co-design marks a significant step forward in DSP technology. By leveraging its extended Single Instruction, Multiple Data (SIMD) capabilities alongside features like a double-precision floating-point unit (DP_FPU), the HiFi 5s delivers unparalleled precision and speed improvements in signal and audio processing tasks. Equally notable are its branch prediction and L2 cache enhancements, which optimize system performance by refining the control code execution and recognizing codec efficiency. The application of such enhancements are particularly beneficial in real-world scenarios.

AI-Powered Audio

Cadence's focus on AI integration with the HiFi 5s demonstrates significant improvements in audio clarity through AI-powered solutions.

• AI models learn from real-world data and adapt dynamically, while classic DSP algorithms rely on fixed rules.
• AI can be fine-tuned for specific scenarios, whereas classic DSP lacks flexibility.
• AI handles extreme and marginal noise patterns better, generalizes well across different environments, and is robust against varying noise characteristics.

Cadence's dedication to artificial intelligence marks a pivotal shift in audio processing. Traditional DSP algorithms, bound by rigid rules, are eclipsed by AI's ability to learn dynamically from real-world data. This adaptability equips AI models to tackle challenging noise patterns and offer unmatched clarity even in noisy environments, making them ideal for automotive and consumer audio applications.

Realtime AI-Optimized Speech Enhancements by OmniSpeech and ai|coustics

OmniSpeech

Our partner, OmniSpeech, has advanced AI-based audio processing that enhances the performance of audio software, specifically for omnidirectional and dipole microphones. Impressively, their technology operates with less than 32MHz and requires only 418kB of memory.

Test results show that background noise is significantly reduced when AI employs a single omnidirectional microphone, outperforming non-AI solutions. Additionally, when using a dipole microphone with AI, there is a 3.5X improvement in the weighted Signal-to-Noise Ratio (SNR) and more than a 28% increase in the Global Mean Opinion Score (GMOS) across various background noise.

ai|coustics

ai|coustics, a Cadence partner specializing in advanced audio technologies, utilizes real-time AI-optimized speech enhancement algorithms. They leverage an extensive speech-quality dataset containing thousands of hours and 100 languages to transform low-quality audio into studio-grade audio. Their process includes:

• De-reverb, which eliminates room resonances, echoes, and reflections

• Removing artifacts from downsampling and codec compression

• Dynamic and adaptive background noise removal

• Reviving audio materials with analog and digital distortions

• Providing support for all languages, accents, and a variety of speakers

Applications include:

• Automotive: Enhances clarity of navigation commands and communication for driver safety

• Consumer audio: Improves voice clarity for better dialogue understanding in TV programs. Optimizes speech intelligibility in communication for both uplink and downlink audio streams

• Smart IoT: Boosts voice command detection and response quality

Performance Enhancements

The advancements in branch prediction and L2 cache integration have significantly boosted performance metrics across various systems. With HiFi 5s, branch prediction increases codec efficiency by an average of 5%, reaching up to 16% in optimal conditions. L2 cache improvements have drastically enhanced system-level performance, evidenced by a 2.3X boost in EVS decoder efficiency. Adding MACs and imaging ISA in imaging use cases has led to substantial advancements. When comparing HiFi 5s to HiFi 5, imaging ISA performance improvements range with >60% average performance improvements.

The Crescendo of the Future

As Cadence continues to blaze trails in DSP technology, the HiFi 5s emerges as the quintessential solution for consumer and automotive audio use cases. With a robust framework for auto-vectorization, an unmatched double-precision FPU, AI-driven audio solutions, and comprehensive system enhancements, Cadence is orchestrating the next era of audio processing, where every note is clearer, every sound richer, and every experience more engaging. It is not just the future of audio—it's the future of how we experience the world around us.

 Discover how Cadence Automotive Solutions can transform your business today!

LEF allows the same port with multiple shape definitions. Does anybody know if innovus can create multiple duplicate shapes associated with the same port? Assume they are connected outside the block with perfect timing synchronization. Thank you!

I am working with innovus on a huge design. I found some cells are placed far away from both timing start points and timing end points. I suspect some other timing paths may be near-critical that results in this sub-optimal cell placement; or innovus has to place the cell far away due to congestion of placement or routing.

Is there a way to see why innovus places/moves the cell during place_opt_design or ccopt_design?

Also, is there a way to highlight all timing start points or timing end points that go through a cell? There may be thousands of timing paths through this cell. I tried using report_timing and timing debugger but it is very painful to click the highlight box and highlight the timing paths one by one.

Thank you for your help!

Hi everyone,

I'm designing a digital chip that will be fabricated. I have a HDL top module that includes several submodules inside it. I want to define the position of some of the submodules during the PnR so that later I can specify there positions in the Micrograph photo after the IC fabrication. When I perform the PnR using Innovus, I always got a layout shape where the submodules seems to be flatted. I wonder if there is a way to specify the placement of each submodule in my top module  (maybe in the tcl file) during the PnR so later I can define there positions in the micrograph photo. 

Thanks in Advance!

Hi all,

I have off grid violations on M2 layer. I have tried ecoRoute -fix_drc and deleting violations and rerouting. But the tool is still placing these routes off grid. The on grid option in nanoroute is turned on. Since there is a fat metal closer to these routes, the tool is honouring the drc and not placing the metals on track. How do I ignore drc while routing? Also if there is any other way I can fix it, please let me know 

Hello Community,

Is there any simple way how i can get the coordinates of all the shapes in a layout view?

Currently i'm flattening the layout, getting all the lpps from CV and using setof to get all the shapes of a layer and looping through them to get the coordinates.

Is there a way to do it without having to flatten the layout view and shapes merged or any other elegant way to do it if we flatten it?

Also, dbWriteSkill doesn't give output how i desired

Thanks,

Shankar

Hi,

I want to define a procedure that with @key, and I also want to restrict the variable's datatype, I tried with folloing but I received error in CIW

procedure(tt(handler @key str1 str2 "ssS")
  printf("handler: %L " handler)
)

tt('test)

The error is like: *Error* tt: argument for keyword ?str1 should be a symbol (type template = "ssS") at line 11 of file

Thanks,

James

Hello,

I was looking to destructively and efficiently modify a list that was passed in as an argument to a procedure, by prepending an item to the list.

I noticed that cons lets you do this efficiently, but the operation is non-destructive. Hence this wouldn't work if you are trying to modify a function's list parameter in place.

Here is an example of trying to add "0" to the front of a list:

Cadence AWR Design Environment Software Featured in Multiple Training Course Options: Live and Virtual Starting in October(read more)

The Cadence AWR Design Environment V22.1 production release is now available for download at Cadence Downloads with design environment, AWR Microwave Office, AWR VSS, AWR Analyst, and other enhancements.(read more)

Microwave Office is Cadence’s tool-of-choice for RF and microwave designers designing everything from III-V 5G chips, to RF systems in board and package technologies. These types of designs require close interaction between the schematic and its layout. A new Training Byte demonstrates how the schematic-layout connections is built into Microwave Office.(read more)

Data sets are a powerful and easy-to-use feature in Microwave Office. Data can be effortlessly be swapped in graphs, and circuit schematics.(read more)

A training webinar on Microwave Office will be given June 27, 2023. The emphasis will be on EM simulation.(read more)

A recording of a training webinar on Microwave Office is available. Topics show the design environment, with special emphasis placed on electromagnetic (EM) simulation. Normal 0 false false false EN-US JA X-NONE ...(read more)

New online training course for AXIEM EM Simulator in AWR Microwave Office is available.(read more)

Hi,

I have synthesized a verilog code. When performing the pnr in innovus it is showing the error "Instance g5891__718 (similar for other) of the cell AND2_X6 has no physical library or has wrong dimension  values (<=0). Check your design setup to make sure the physical library is loaded in and attribute specified in library are correct.

When importing synthesized netlist in virtuoso then it says " Module AND2_X6, instantiated in the top module decoder, is not defined. Therefore the top module decoder will be imported as functional."

Please help what's going on here? 

Hi Cadence, 

I use simvision 20.09-s007 but my computer screen resolution is very high. As a result, the texts are too small. 

In ~/.simvision/Xdefaults I changed that number to 16, from 12. But the signal names in the waveform traces don't reflect the change. 

Simvision*Font: -adobe-helvetica-medium-r-normal--16-*-*-*-*-*-*-*

Other .font changes seem to reflect on the simvision correctly, except the signal names. 

How do I fix that? I dont mind a single variable to change all the texts fonts to 16. 

Thank you!

PS: I found the answer with another post. I change Preference/Waveform/Display/Signal Height. 

I am not able to open 64bit version of simvision using the following :

simvision -64 -wav "path to wav"

This throws the error "  /lib64/libc.so.6: version `GLIBC_2.14' not found"

I am only able to open it without the -64 option.

As a result I am not able to use the source browser feature since the simulation was run in 64 bit mode.

Need suggestion on how to resolve this. Thanks.

Hello,

I am trying to load some of the signals of the design saved in the signals.svwf to the waveform windown via the tcl file, I am using the following commands but nothing works, Can you please help 

 -submit waveform loadsignals -using "Waveform 2" FB1.svwf but it gives me the below error

-submit waveform new -reuse -name Waveforms

hi

How can I tell the LEC tool to ignore a combination of Primary input bus in both Golden and revised.

For example in both Golden and revised there is 

input [3:0] data_in

I want LEC not to check the case that data_in[3:0] == 4'b1000

I am trying to understand the Linting process. I know that mainly JasperGold is the tool for this purpose. Though I think JasperGold is more suited for later stages of the design. As a RTL Design Engineer, I want to make sure that if another tool has the capability of doing Linting earlier in the flow. for example, does Xcelium, Genus or Confomal support linting. I have seen some contradicting information online regarding this topic, though I can't find anything related to Linting on any of these tools.

Thanks

Hi. I'm a very new learner on Cadence. I want to synthesis my logic design for the maximum, minimum and an average results of delay, power dissipation and area under varying multiple inputs of different data. The different data will be exported from other software results. I'm lost on the steps/processes I should do.

Could anyone suggest me on which software and/or function or scripts I should use to achieve these results?