Read the in depth Review of Realme Buds Air 3S Audio Video. Know detailed info about Realme Buds Air 3S configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of AIWA MI-X330 Meteor Audio Video. Know detailed info about AIWA MI-X330 Meteor configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of Apple AirPods Pro (2nd generation) Audio Video. Know detailed info about Apple AirPods Pro (2nd generation) configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of Oppo Enco Air3 Audio Video. Know detailed info about Oppo Enco Air3 configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of AIWA RS-X 150 Natsukasii Pro Audio Video. Know detailed info about AIWA RS-X 150 Natsukasii Pro configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of OPPO Enco Air3 Pro Audio Video. Know detailed info about OPPO Enco Air3 Pro configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of realme Buds Air 5 Pro Audio Video. Know detailed info about realme Buds Air 5 Pro configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

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You can now port from Airtel to Jio and vice versa through these easy 4 steps.

I am gratified to see the continuing adoption of Forecast Value Added by organizations worldwide. FVA is an easy to understand and easy to apply approach for identifying bad practices in your forecasting process. And I'm particularly gratified to see coverage of FVA in two new books, which the authors [...]

The post Vandeput's Data Science for Supply Chain Forecasting (book excerpt) appeared first on The Business Forecasting Deal.

With containers, you can build once, run anywhere – no worries about underlying dependencies.

The post How containers have moved us to next-gen virtualization appeared first on The Data Roundtable.

The Congress will begin a month-long 'Delhi Nyay Yatra' from Rajghat on Friday to corner the Aam Aadmi Party government on various issues affecting the city.

A year-old murder case has been re-opened in Uttar Pradesh's Meerut after a hired killer, who is out on bail, approached the police for not being paid a ransom for the job.

In a horrifying incident at a fair in Kannauj, Uttar Pradesh, a teenage girl's hair became entangled in the roller of a swing, resulting in her entire scalp being ripped out.

A Bengaluru couple found themselves in legal trouble after they posted videos of their balcony garden on Facebook. The posts included images of plants later identified as ganja.

A body of a man has been found in a plastic bag in seven pieces on Mumbai's Gorai beach, the police said today.

Police on Monday arrested Manisha, wife of jailed gangster Kaushal Chaudhary, for allegedly trying to extort Rs 2 crores from a hotel owner, officials said.

A man was on Monday arrested for driving his car, a Mahindra Thar, on a railway track in Rajasthan's Jaipur. The man, said to be drunk, had taken his SUV on to railway tracks to shoot a reel for social media.

A suspended teacher from the PSBB (Padma Seshadri Bala Bhavan) School in Chennai has been sentenced to two years of rigorous imprisonment for sexually harassing female students.

Ratan Naval Tata, the business titan and global icon who led the Tata behemoth from thirty countries to over a hundred since becoming chairman in 1991, died today at Mumbai's Breach Candy Hospital. He was 86.

Ratan Tata, born on December 28, 1937, is the Chairman of Ratan Tata Trust, two of the largest private-sector-promoted philanthropic trusts in India.

1. Has AIMIM’s Owaisi, the dark horse in Maharashtra elections, played a winning move?  Hindustan Times
2. Video | Maharashtra Election Will Throw Up Fractured Mandate: A Owaisi's Party Leader  NDTV
3. Owaisi backs Maratha reservation ahead of Maharashtra Assembly polls  India Today
4. Need to fight unitedly by Muslims, Maratha and Dalits: Barrister Owaisi.  Etemaad
5. No one can say Uddhav Thackrey won't go back to BJP: AIMIM  The Times of 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. Doctor Stabbed 7 Times By Patient's Son In Chennai Hospital  NDTV
2. Chennai doctor stabbed by assilants posing as patients  The Times of India
3. Patient's son stabs doctor 7 times in Chennai hospital, arrested  India Today
4. 25-year-old stabs doctor at Chennai hospital, four detained  Deccan Herald
5. Doctor stabbed at Kalaignar Centenary Super Speciality Hospital in Chennai; one arrested  The Hindu

1. Chennai rain: IMD predicts heavy rainfall for Tamil Nadu. Are schools, colleges closed today?  Hindustan Times
2. Chennai rains today: Heavy downpour expected in many Tamil Nadu districts, IMD issues alert. Schools shut today?  Mint
3. Low pressure weakens, but heavy rain in Tamil Nadu may persist  The New Indian Express
4. Tamil Nadu weather: Schools shut in Chennai, IMD puts 17 districts in state on heavy rainfall alert  Business Today
5. Tamil Nadu rains: Schools, colleges closed in several districts amid heavy rain  The Hindu

1. Delhi: India's capital chokes as air pollution turns 'severe'  BBC.com
2. Several flights diverted due to low visibility conditions at Delhi airport  The Times of India
3. Delhi's toxic air: Why you should not take your cough lightly  India Today
4. Delhi air pollution: Visibility near-zero amid thick smog; CPCB says AQI 'very poor', IQAir shows 'hazardous' | Details  Hindustan Times
5. Delhi's IGI airport sees flight diversions as season's first dense fog hits national capital  Moneycontrol

Google has seemingly launched the Quick Share app for Windows on ARM PCs, something that was not previously available.

The post Google Quick Share now available for Windows on ARM appeared first on Phandroid.

The post details a highly restrictive environment where employees are forbidden from basic actions like looking away from their screens or using their phones.

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.

[SAnews.gov.za] Twenty-three people in Gauteng have died as a result of food borne-related poisoning after consuming food from spaza shops.

[Premium Times] In September, Tyla made headlines at the MTV Video Music Awards (VMAs) for winning the "Best Afrobeats," but she stirred debate by clarifying that she identified with the Amapiano genre rather than Afrobeats

[allAfrica]

[GroundUp] The education department says there's only one SETA official assisting all nine provinces

The generative AI market is experiencing rapid growth, driven by the increasing parameter size of Large Language Models (LLMs). This growth is pushing the boundaries of performance requirements for training hardware within data centers. For an in-depth look at this, consider the insights provided in "HBM3E: All About Bandwidth". Once trained, these models are deployed across a diverse range of applications. They are transforming sectors such as finance, meteorology, image and voice recognition, healthcare, augmented reality, high-speed trading, and industrial, to name just a few.

The critical process that utilizes these trained models is called AI inference. Inference is the capability of processing real-time data through a trained model to swiftly and effectively generate predictions that yield actionable outcomes. While the AI market has primarily focused on the requirements of training infrastructure, there is an anticipated shift towards prioritizing inference as these models are deployed.

The computational power and memory bandwidth required for inference are significantly lower than those needed for training. Inference engines typically need between 300-700GB/s of memory bandwidth, compared to 1-3TB/s for training. Additionally, the cost of inference needs to be lower, as these systems will be widely deployed not only in data centers but also at the network's edge (e.g., 5G) and in end-user equipment like security cameras, cell phones, and automobiles.

When designing an AI inference engine, there are several memory options to consider, including DDR, LPDDR, GDDR, and HBM. The choice depends on the specific application, bandwidth, and cost requirements. DDR and LPDDR offer good memory density, HBM provides the highest bandwidth but requires 2.5D packaging, and GDDR offers high bandwidth using standard packaging and PCB technology.

The GDDR7 standard, announced by JEDEC in March of this year, features a data rate of up to 192GB/s per device, a chip density of 32Gb, and the latest data integrity features. The high data rate is achieved by using PAM3 (Pulse Amplitude Modulation) with 3 levels (+1, 0, -1) to transmit 3 bits over 2 cycles, whereas the current GDDR6 generation uses NRZ (non-return-to-zero) to transmit 2 bits over 2 cycles.

GDDR7 offers many advantages for AI Inference having the best balance of bandwidth and cost. For example, an AI Inference system requiring 500GB/s memory bandwidth will need only 4 GDDR7 DRAM running at 32Gbp/s (32 data bits x 32Gbp/s per pin = 1024Gb/s per DRAM). The same system would use 13 LPDDR5X PHYs running at 9.6Gbp/s, which is currently the highest data rate available (32 data bits x 9.6Gb/s = 307Gb/s per DRAM).

Cadence stands at the forefront of AI inference hardware support, being the first IP company to roll out GDDR7 PHYs capable of impressive speeds up to 36Gb/s across various process nodes. This milestone builds on Cadence's established leadership in GDDR6 PHY IP, which has been available since 2019. The company caters to a diverse client base spanning AI inference, graphics, automotive, and networking equipment.

While GDDR7 continues to utilize standard PCB board technology, the increased signal speeds seen in GDDR6 (20Gbp/s) and now GDDR7 (36Gb/s) calls for careful attention with the physical design to ensure optimized system performance. In addition to providing the PHY, Cadence also offers comprehensive PCB and package reference design, which are essential in helping customers achieve optimal signal and power integrity (SI/PI) for their systems.

Cadence is dedicated to ensuring customer success beyond just providing hardware. They provide expert support in SI/PI, collaborating closely with customers throughout the design process. This approach ensures that customers can benefit from Cadence's expertise in navigating the complexities of high-speed design and achieving optimal performance in their AI inference systems.

As the AI market continues to advance, Cadence remains at the forefront by offering a comprehensive memory IP portfolio tailored for every segment of this dynamic market. From DDR5 and HBM3E, which cater to the intensive demands of training in servers and high-performance computing (HPC), to LPDDR5X designed for low-end inference at the network edge and in consumer devices, Cadence's offerings cover a wide range of applications.

Looking to the future, Cadence is dedicated to innovating at the forefront of memory system performance, ensuring that the evolving needs of AI training and inference are met with the highest standards of excellence. Whether it's pushing the boundaries with GDDR7 or exploring new technologies, Cadence is dedicated to driving the AI revolution forward, one breakthrough at a time.

Learn more about Cadence GDDR7 PHY

Learn more about Cadence Simulation VIP for GDDR7.

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!

I am trying to install IC231 on RHEL 8 using installscape, however configuring keeps failing.

I tried to run the configuration file manually as suggested in one of the previous posts and it gives me following errors:

sh batch_configure.sh
/home/rs/cadence/installs/IC231/install/tmp/slconfig.sh: line 165: xterm: command not found
cat: ncvhdl23.03-d103lnx86_101124125631.stat: No such file or directory
rm: cannot remove 'ncvhdl23.03-d103lnx86_101124125631.stat': No such file or directory
/home/rs/cadence/installs/IC231/install/tmp/slconfig.sh: line 165: xterm: command not found
cat: ncvhdl64b23.03-d103lnx86_101124125631.stat: No such file or directory
rm: cannot remove 'ncvhdl64b23.03-d103lnx86_101124125631.stat': No such file or directory
/home/rs/cadence/installs/IC231/install/tmp/slconfig.sh: line 165: xterm: command not found
cat: oaRedist22.61-p003lnx86_101124125631.stat: No such file or directory
rm: cannot remove 'oaRedist22.61-p003lnx86_101124125631.stat': No such file or directory
/home/rs/cadence/installs/IC231/install/tmp/slconfig.sh: line 165: xterm: command not found
cat: amsEnv64b23.10-p043lnx86_101124125631.stat: No such file or directory
rm: cannot remove 'amsEnv64b23.10-p043lnx86_101124125631.stat': No such file or directory
/home/rs/cadence/installs/IC231/install/tmp/slconfig.sh: line 165: xterm: command not found
cat: ihdl64b23.10-p043lnx86_101124125631.stat: No such file or directory
rm: cannot remove 'ihdl64b23.10-p043lnx86_101124125631.stat': No such file or directory

I am not very well versed with Linux at the moment but trying. Could any one suggest something or point to what is missing?

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