Samsung has an early Black Friday deal for its accessories and wearables, so don’t miss out if you want some savings!

The post INCREDIBLE early Black Friday deal saves you on Samsung wearables and accessories! appeared first on Phandroid.

The headphones come with a rather lightweight design, Sony's integrated V1 processor and noise-cancelling duties.

The post Save up to 40% with the Sony WH-CH720N Headphones! appeared first on Phandroid.

If you're an iPhone user, then you might want to check the Chrome app for new updates.

The post Google Adds Some Nifty Features for Chrome on iOS Devices appeared first on Phandroid.

Valve says that customers are limited to one purchase per account.

The post You can Soon Get the Steam Deck OLED in White, but You’d Better Hurry appeared first on Phandroid.

Shared by Gator Boys star Paul Bedard, the viral video shows the alligator emerging from his den to the tune of the iconic song.

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.

Owlet, a connected-baby care company raised a $24 million Series B investment from Trilogy Equity Partners, with participation from existing investors, including Eclipse Ventures, Broadway Angels, and Enfield Ventures, and the addition Pelion Venture Partners.

Owlet’s core product is a baby sock that contains a smart sensor. The sensor monitors pulse oximetry, a technology used in hospitals to measure an infant's heart rate and blood oxygen levels. The vital signs are communicated to parents’ smartphone via Bluetooth connection. The product retails for $299 and parents can also choose from monthly payment plans.

Other IoT-health startups using sensors to monitor vital signs include Aifloo, a company selling wrist-bands for elders and Air by Propeller, a smart health company that provides an API to predict local asthma conditions.

A complete product package of Owlet monitor includes three fabric socks, smart sock sensor, a base station (which rings an alarm if a baby’s vital signs are abnormal), and charging cords.

Before the company raised the latest round, it closed a $15 million Series B round in late 2016. The recent investment brought Owlet’s total equity funding to $46M. Owlet plans to use the growth capital to launch more baby care products.

Vesper, the maker of piezoelectric sensors used in microphone production and winner of CES Innovation Award 2018 raised a $23M Series B round. American Family Ventures led the investment with participation from Accomplice, Amazon Alexa Fund, Baidu, Bose Ventures, Hyperplane, Sands Capital, Shure, Synaptics, ZZ Capital and some undisclosed investors.

Vesper’s innovative sensors can be used in consumer electronics like TV remote controls, smart speakers, smartphones, intelligent sensor nodes, and hearables. The company will use the funding proceeds to scale-up its functions like mass production of its microphones and support expanded research and development, hiring, and establishing international sales offices.

The main product of Vesper is VM1000, a low noise, high range,single-ended analog output piezoelectric MEMS microphone. It consists of a piezoelectric sensor and circuitry to buffer and amplify the output.

The hot-selling product of Vesper is VM1010 with ZeroPower Listening which is the first MEMS microphone that enables voice activation to battery-powered consumer devices.

The unique selling point of Vesper’s products is they are built to operate in rugged environments that have dust and moisture.

"Vesper's ZeroPower Listening capabilities coupled with its ability to withstand water, dust, oil, and particulate contaminants enables users that have never before been possible," said Katelyn Johnson, principal of American Family Ventures. "We are excited about Vesper's quest to transform our connected world, including IoT devices."

Other recent funding news include $24 raised by sensor-based baby sock maker Owlet, IFTTT banks $24M from Salesforce to scale its IoT Enterprise offering, and Intel sells its Wind River Software to TPG.

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.

This new Corporate Social Responsibility (CSR) Practices in India Report 2020 is a must read

[SAPS] - The Acting Provincial Commissioner of the SAPS in Mpumalanga Major General (Dr) Zeph Mkhwanazi has welcomed the 15 years imprisonment term handed down to Bongani Motha (24) by Middleburg Regional Court on Wednesday, 05 November 2024.

[The Conversation Africa] South Africa's finance minister, Enoch Godongwana, announced in his October mid-term budget policy statement that cabinet had approved funding for an early retirement programme to reduce the public sector wage bill. R11 billion (about US$627 million) will be allocated over the next two years to pay for the exit costs of 30,000 civil servants while retaining critical skills and promoting the entry of younger talent.

[DA] Note to editors: Please find attached soundbite by Ian Cameron MP.

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

[State Department] U.S. Ambassador-at-Large to Monitor and Combat Trafficking in Persons Cindy Dyer will travel to Madagascar November 13-16 and South Africa November 17-21.

[allAfrica]

[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.

[Namibian] Russian company Rosatom and South African AllWeld Nuclear and Industrial are joining forces to promote the sustainable development of nuclear energy in Africa.

[allAfrica]

[The Conversation Africa] Despite the flaws in the latest novel by South African writer Nthikeng Mohlele, there is something alluring about Revolutionaries' House. It is Mohlele's most political novel, and the parallels drawn between love and politics - and their pitfalls - are intriguing.

PCI-SIG DevCon 2024 – 32^nd Anniversary

For more than a decade, Cadence has been well-known in the industry for its strong commitment and support for PCIe technology. We recognize the importance of ensuring a robust PCIe ecosystem and appreciate the leadership PCI-SIG provides. To honor the 32^nd anniversary of the PCI-SIG Developer’s Conference, Cadence is announcing a complete PCIe 7.0 IP solution for HPC/AI markets.

Why Are Standards Like PCIe So Important?

From the simplest building blocks like GPIOs to the most advanced high-speed interfaces, IP subsystems are the lifeblood of the chipmaking ecosystem. A key enabler for IP has been the collaboration between industry and academia in the creation of standards and protocols for interfaces. PCI-SIG drives some of the key definitions and compliance specifications and ensures the interoperability of interface IP.

HPC/AI markets continue to demand high throughput, low latency, and power efficiency. This is fueling technology advancements, ensuring the sustainability of PCIe technology for generations to come. As a close PCI-SIG member, we gain valuable early insights into the evolving specs and the latest compliance standards. PCIe 7.0 specifications and beyond will enable the market to scale, and we look forward to helping our customers build best-in-class cutting-edge SoCs using Cadence IP solutions.

Figure 1. Evolution of PCIe Data Rates (source PCI-SIG)

What’s New This Year at DevCon?

At DevCon ’24, the PCIe 7.0 standard will take center stage, and Cadence is showing off a full suite of IP subsystem solutions for PCIe 7.0 this year.

What Sets Cadence Apart?

At Cadence, we believe in building a full subsystem for our testchips with eight lanes of PHY along with a full 8-lane controller. Adding a controller to our testchip significantly increases the efficiency and granularity in characterization and stress testing and enables us to demonstrate interoperability with real-world systems. We are also able to test the entire protocol stack as an 8-lane solution that encompasses many of the applications our customers use in practice. This approach significantly reduces the risks in our customers’ SoC designs.

Figure 2: Piper - Cadence PHY IP for PCIe 7.0

Figure 3: Industry’s first IP subsystem for PCIe 7.0

Which Market Is This For?

At a time when accelerated computing has gone mainstream, PCIe links are going to take on a role of higher importance in systems. Direct GPU-to-GPU communication is crucial for scaling out complex computational tasks across multiple graphics processing units (GPUs) or accelerators within servers or computing pods. There is a growing recognition within the industry of a need for scalable, open architecture in high-performance computing. As AI and data-intensive applications evolve, the demand for such technologies will likely increase, positioning PCIe 7.0 as a critical component in the next generation of interface IP.

Here's a recent article describing a potential use case for PCIe 7.0.

Figure 4: Example use case for PCIe 7.0

Why Are Optical Links Important?

It takes multiple buildings of data centers to train AI/ML models today. These buildings are increasingly being distributed across geographies, requiring optical fiber networks that are great at handling the increased bandwidth over long distances. However, these optical modules soon hit a power wall where all the budgeted power is used to drive the signal from point A to point B, and there is not enough power left to run the actual CPUs and GPUs. Such scenarios create a need for non-retimed, linear topologies. Linear Pluggable Optics (LPO) links can significantly reduce module power consumption and latency when compared to traditional Digital Signal Processing (DSP) based retimed optical solutions, which is critical for accelerating AI performance. Swapping from DSP-based solutions to LPO results in significant cost savings that help drive down expenditure due to lower power and cooling requirements, but this requires a robust high-performance ASIC to drive the optics rather than retimers/DSP.

To showcase the robustness of Cadence IP, we have demonstrated that our subsystem testchip board for PCIe 7.0 can successfully transmit and receive 128GT/s signals through a non-retimed opto-electrical link configured in an external loopback mode with multiple orders of margin to spare.

Figure 5: Example of ASIC driving linear optics

Compliance Is Key

For PCIe 6.0, the official compliance program has not started yet; this is typical for the SIG where the official compliance follows a few years after the spec is ratified to give enough time for the ecosystem to have initial products ready, and for test and equipment vendors to get their hardware/software up and running. At this time, PCIe Gen6 implementations can only be officially certified up to PCIe 5.0 level (the highest official compliance test suite that the SIG supports). We have taken our PCIe 6.0 IP subsystem solution to the SIG for multiple process nodes, and they are all listed as compliant. You can run this query on the pcisig.com website under the Developers->Integrators list by making the following selections:

Due to space limitations, not all combinations could be tested at the May workshop (e.g., N3 root port) – this will be tested in the next workshop.

Also, the SIG just held an “FYI” compliance event this week to bring together the ecosystem for confidential testing (no results were reported, and data cannot be shared outside without violating the PCI-SIG NDA). We participated in the event with multiple systems and can report that our systems have done quite well. The test ecosystem is not mature yet, and a few more FYI workshops will be conducted before the official compliance for 6.0 is launched. We have collaborated with all the key test vendors for electrical and protocol testing throughout the year. As early as the middle of last year, we were able to provide test cards to all these vendors to demo PCIe 6.0 capabilities in their booths at various events. Many of them recorded these videos, and they can be found online.

• Cadence Subsystem IP for PCIe 6.0: Protocol and Electrical Testing
• Cadence Subsystem IP for CXL Protocol Test Demo
• Cadence Subsystem IP for CXL2.0/3.0 Protocol Test Demo
• Cadence Subsystem IP for PCIe 6.0: Protocol Stack Demo

More at the PCI-SIG Developers Conference

Check us out at the PCI-SIG Developer’s conference on June 12 and 13 to see the following demonstrations:

• Robust performance of Cadence IP for PCIe 7.0 transmitting and receiving 128GT/s signals over non-retimed optics
• Capabilities of Cadence IP for PCIe 7.0 measured using oscilloscope instrumentation detailing its stable electrical performance and margin
• The reliability of Cadence IP for PCIe 6.0 interface using Test Equipment to characterize the PHY receiver quality
• A PCI-SIG-compliant Cadence IP subsystem for PCIe 6.0 optimized for both power and performance

As a leader in PCI Express, Anish Mathew of Cadence will share his valuable insights on an important topic: “Impact of UIO ECN on PCIe Controller Design and Performance,” highlighting the strides made by the Cadence design team in achieving this implementation.

Figure 6: Cadence UIO Implementation Summary

Summary

Cadence showcased PCIe 7.0-ready IP at PCI-SIG Developers Conference 2023 and continues to lead in PCIe IP development, offering complete solutions in advanced nodes for PCIe 7.0 that will be generally available early next year. With a full suite of solutions encompassing PHYs, Controllers, Software, and Verification IP, Cadence is proud to be a member of the PCI-SIG community and is heavily invested in PCIe. Cadence was the first IP provider to bring complete subsystem solutions for PCIe 3.0, 4.0, 5.0, and 6.0 with industry-leading PPA and we are proud to continue this trend with our latest IP subsystem solution for PCIe 7.0, which sets new benchmarks for power, performance, area, and time to market.

The automotive industry is currently on the cusp of a radical evolution, steering towards a future where cars are not just vehicles but sophisticated, software-defined vehicles (SDV). This shift is marked by an increased reliance on automation and a significant increase in the use of sensors to improve safety and reliability. However, the increasing number of sensors has led to higher compute demands and poses challenges in managing a wide variety of data. The traditional method of using separate processors to manage each sensor's data is becoming obsolete. The current trends necessitate a unified processing system that can deal with multimodal sensor data, utilizing traditional Digital Signal Processing (DSP) and AI-driven algorithms. This approach allows for more efficient and reliable sensor fusion, significantly enhancing vehicle perception. Developers often face difficulties adhering to stringent power, performance, area, and cost (PPAC) and timing constraints while designing automotive SoCs.

Cadence, with its groundbreaking products and AI-powered processors, is enabling designers and automotive manufacturers to meet the future sensor fusion demands within the automotive sector. At the recent CadenceLive Silicon Valley 2024, Amol Borkar, product marketing director at Cadence, showcased the company's dedication and forward-thinking solutions in a captivating presentation titled "Addressing Tomorrow’s Sensor Fusion Needs in Automotive Computing with Cadence." This blog aims to encapsulate the pivotal takeaways from the presentation. If you missed the chance to watch this presentation live, please click here to watch it.

Significant Trends in the Automotive Market – Industry Landscape

We are witnessing a revolution in automotive technology. Innovations like occupant and driver monitoring systems (OMS, DMS), 4D radar imaging, LiDAR technology, and 360-degree view are pushing the boundaries of what's possible, leading us into an era of remarkable autonomy levels—ranging from no feet or hands required to eventually no eyes needed on the road.

Sensor Fusion and Increasing Processing Demands—Sensor fusion effectively integrates data from different sensors to help vehicles understand their surroundings better. Its main benefit is in overcoming the limitations of individual sensors. For example, cameras provide detailed visual information but struggle in low-light or lousy weather. On the other hand, radar is excellent at detecting objects in these conditions but lacks the detail that cameras provide. By combining the data from multiple sensors, automotive computing can take advantage of their strengths while compensating for their weaknesses, resulting in a more reliable and robust system overall.

One thing to note is that the increased number of sensors produces various data types, leading to more pre-processing.

On-Device Processing—As the industry moves towards autonomy, there is an increasing need for on-device data processing instead of cloud computing to enable vehicles to make informed decisions. Embracing on-device processing is a significant advancement for facilitating real-time decisions and avoiding round-trip latency.

AI Adoption—AI has become integral to automotive applications, driving safety, efficiency, and user experience advancements. AI models offer superior performance and adaptability, making future-proofing a crucial consideration for automotive manufacturers. AI significantly enhances sensor fusion algorithms, offering scalability and adaptability beyond traditional rule-based approaches. Neural networks enable various fusion techniques, such as early fusion, late fusion, and mid-fusion, to optimize the integration and processing of sensor data.

Future Sensor Fusion Needs

Automotive architectures are continually evolving. With current trends and AI integration into radar and sensor fusion applications, SoCs should be modular, flexible, and programmable to meet market demands.

Heterogeneous Architecture- Today's vehicles are loaded with various sensors, each with a unique processing requirement. Running the application on the most suitable processor is essential to achieve the best PPA. To meet such requirements, modern automotive solutions require a heterogeneous compute approach, integrating domain-specific digital signal processors (DSPs), neural processing units (NPUs), central processing unit (CPU) clusters, graphics processing unit (GPU) clusters, and hardware accelerator blocks. A balanced heterogeneous architecture gives the best PPA solution.

Flexibility and Programmability- The industry has come a long way from using computer vision algorithms such as HOG (Histogram Oriented Gradient) to detect people and objects, HAR classifier to detect faces, etc., to CNN and LSTM-based AI to Transformer models and graphical neural networks (GNN). AI has evolved tremendously over the last ten years and continues to evolve. To keep up with the evolving rate of AI, SoC design must be flexible and programmable for updates if needed in the future.

Addressing the Sensor Fusion Needs with Cadence

Cadence offers a complete suite of hardware and software products to address the increasing compute requirements in automotive. The comprehensive portfolio of Tensilica products built on the robust 32-bit RISC architecture caters to various automotive CPU and AI needs. What makes them particularly appealing is their scalability, flexibility, and configurability, offering many options to meet diverse needs.

The Xtensa family of products offers high-quality, power-efficient CPUs. Tensilica family also includes AI processors like Neo NPUs for the best power, performance, and area (PPA) for AI inference on devices or more extensive applications. Cadence also offers domain-specific products for DSPs such as HIFI DSPs, specialized DSPs and accelerators for radar and vision-based processing, and a general-purpose family of products for floating point applications.

The ConnX family offers a wide range of DSPs, from compact and low-power to high-performance, optimized for radar, lidar, and communications applications in ADAS, autonomous driving, V2X, 5G/LTE/4G, wireless communications, drones, and robotics. Tensilica's ISO26262 certification ensures compliance with automotive safety standards, making it a trusted partner for advanced automotive solutions. The Cadence NeuroWeave Software Development Kit (SDK) provides customers with a uniform, scalable, and configurable ML interface and tooling that significantly improves time to market and better prepares them for a continuously evolving AI market. Cadence Tensilica offers an entire ecosystem of software frameworks and compilers for all programming styles.

Tensilica's comprehensive software stack supports programming for DSPs, NPUs, and accelerators using C++, OpenCL, Halide, and various neural network approaches. Middleware libraries facilitate applications such as SLAM, radar processing, and Eigen libraries, providing robust support for automotive software development.

Conclusion

Cadence’s Tensilica products offer a development toolchain and various IPs tailored for the automotive industry, covering audio, vision, radar, unified DSPs, and NPUs. With ISO certification and a robust partner ecosystem, Tensilica solutions are designed to meet the future needs of automotive computing, ensuring safety, efficiency, and innovation.

Learn More

• Cadence Automotive Solutions
• Cadence Automotive IP
• Sensor Fusion and ADAS in TSMC Automotive Processes
• Revolution on the Road: How Cadence is Driving the Future of Automotive Design!
• Taming Design Complexity in Chiplet-Based Automotive Electronics
• UCIe and Automotive Electronics: Pioneering the Chiplet Revolution

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.

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!

Hello,

When I draw a Fluid Guard Ring in Virtuoso, the layout is not visible, and instead, "do_something=nil" appears.

When I check the details with Q, it shows the same information as a regular NFGR guard ring, and Ctrl+F also displays the instance name, just like with a regular NFGR. 

Additionally, the Pcells of Fluid Guard Rings from previous projects appear broken. 

The version I’m currently using is not different from the one used in the past. Even when I access the same version as the one used during the project, the Pcells still appear broken.

These two issues are occurring, and I’m not sure what to check. I would greatly appreciate it if you could assist me in resolving this issue.

//

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)

Hello All:

I am looking for help on the following, as I am new to Cadence tools [I have to use Cadence Innovus for Physical Design after Logic Synthesis using Synopsys Design Compiler, using Nangate 45 nm Open Cell Library]: while using Cadence Innovus, I would need to select a few specific nets to be routed through a specific metal layer. How can I do this on Innovus [are there any command(s)]? Also, would writing and sourcing a .tcl script [containing the command(s)] on the Innovus terminal after the Placement Stage of Physical Design be fine for this?

Secondly, is there a way in Innovus to manipulate layout components, such as changing some pin placements, wire directions (say for example, wire direction changed to facing east from west, etc.) or moving specific closely placed cells around (without violating timing constraints of course) using any command(s)/.tcl script? If so, would pin placement changes and constraining some closely placed cells to be moved apart be done after Floorplanning/Powerplanning (that is, prior to Placement) and the wire direction changes be done after Routing? 

While making the necessary changes, could I use the usual Innovus commands to perform Physical Design of the remaining nets/wires/pins/cells, etc., or would anything need modification for the remaining components as well?

I would finally need to dump the entire design containing all of this in a .def file.

I tried looking up but could only find matter on Virtuoso and SKILL scripting, but I'd be using Innovus GUI/terminal with Nangate 45 nm Open Cell Library. I know this is a lot, but I would greatly appreciate your help. Thanks in advance.

Riya

I am scripting gds streamin using 'strmin', which works fine so far.

But, as it apparently doesn't have an option to specify where the cds.lib file is, I have to run it from the directory where the cds.lib file is, or I guess I could create a dummy one to source that one.

Is there a way to tell strmin where the cds.lib file is?

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.

We have a big circuit having 12K gates totally and trying to show it in one page slide visually. But it is so hard for us to shrink it down from gate-level to module-level. Do you have any function like these:

• Toggle wires on and off
• “Right click” elements and group them into black boxes
• Quickly left or right align elements to clean up pictures

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?

The increase in compute and data-intensive applications and the need for lower power consumption have resulted in a rapidly growing number of Arm-based devices in various market segments; this requires fast time to market (TTM) and support for off-t...(read more)

At what stage in the design cycle do you start to think about the PCB material costs? What about the costs to assemble the PCB? Once a design becomes successful, should you then redesign it to achieve a scalable product? Placing components and routi...(read more)

This post was contributed by Liliko Uchida, application engineer at Cadence. Being a “Woman in STEM” is a phrase that has long been used to describe the holistic experience shared by thousands of women globally, yet it still makes us feel isolated. Partially due to the statistics of gender population in the STEM workforce and the remainder due to our own internal obstacles, being a woman in STEM continues to be a challenge. While many of us know the should-do’s and should-be’s of taking on this unique role objectively, we struggle to implement them. After all, our perseverance as engineers, mathematicians, businesswomen, programmers, and scientists is largely affected by subjectivity. The UMass Lowell Women’s Leadership Conference 2024 aimed to tackle this problem by uniting hundreds of women with shared experiences under one roof. Not only did the conference provide us with the knowledge necessary to persevere, but it also gave us the tools that will allow us to thrive and act upon the facts we already know. It is my hope that through this blog post, I can share some of my main takeaways from this special day. Be Confident This is one of the most palpable pieces of advice we always hear. Yet so many of us struggle to build this confidence because we don’t know how. Featured speaker Nicole Kalil defined confidence as “complete trust in oneself”.”One way to build this self-trust is by getting to know yourself on a deeper level. By creating a true inner connection, we begin to see ourselves as a whole instead of hyper-focusing on our shortcomings frequently illusioned by imposter syndrome. In one of the sessions, we were asked to introduce ourselves to our neighbors, not by what we do for work, but by who we are as a person. Even if this opportunity does not arise every day, this practice can be done simply by listing characteristics of yourself that define who you are. Who do you care for? How do you show them? What are your life goals oriented towards? How do you observe others’ behavior around you, and what does that say about how you make them feel? Getting to know you beneath the surface and allowing yourself to be seen for who you are is critical in building internal confidence. With practice, this self-reassurance will grow independent of external factors. Take Risks “Sometimes, you have to put your foot in the elevator” - Barb Vlacich, Keynote Speaker When opportunities arise, the only thing you can do to have a chance is to try. Without putting your foot in the elevator, the doors will close, becoming a missed opportunity. Similarly, several of the conference’s speakers also emphasized that the answer to every unasked question will always be a no. Even if you are not ready to full-send a negotiation, ask for a raise, or respectfully disagree with a co-worker’s opinion, start by getting comfortable asking uncomfortable questions. Just one discomfort a day will help in building an immunity to the anxiety that comes with taking risks, typically driven by our self-doubt. Another interesting point that stood out from the conference was the statistics of self-assessed qualifications between men and women. During the negotiation panel, it was revealed that men typically feel they only need 60% of the qualifications under a job description to apply, whereas women often feel they need close to 100%. These numbers alone demonstrate how the pure mental habits of men continue to funnel them into STEM and not women. The next time you seek a new opportunity, assess yourself based on the 60% and use it as a checklist threshold. If more women are able to pursue STEM careers using these numbers, the more likely we will begin to populate these roles. Build Your Genuine Network “ The essence of communication lies in the mutual exchange of ideas and emotions. And when the listener isn’t invested, it undermines the entire purpose of the conversation. Why are you having it anyway?” This is a quote from episode 186 of Julie Brown’s podcast This Sh!t Works called “The 5 Steps to Being an Active Listener”. Julie Brown is a Networking Coach, author, and podcast host who guided an energetic and candid conversation about networking and building a personal brand for women. Networking is often misunderstood as putting your name and qualifications out on the table for as many people to pick up your cards. While making these things known is important, they are not what nurtures effective connections. The key to cultivating your genuine network is to activate a sincere interest in the people you meet. Become the proactive receiver of the confidence exercise discussed above. When you meet someone new, what can you take away from them as a person, not an employee? By making people feel heard, even through the little conversations, you can begin to develop more meaningful connections that resonate. And, with practice, the sometimes inherent need to overcompensate by defining yourself with your resume will slowly fade. It was a wonderful opportunity to attend the UML Women’s Leadership Conference with four other inspiring Cadence women. Not only was the conference a motivating learning experience, but it was also a wonderful opportunity for us to bond together as women and feel supported by each other. The most eye-opening part of the day was seeing just how many women alike were sitting under the same roof. The conclusion of the event led me to feel proud to be an engineer, proud to be at Cadence, and most importantly, proud to be a woman. Learn more about life at Cadence .

The demand for higher compute performance, energy efficiency, and faster time-to-market drove the conversations at this year's Open Compute Project (OCP) Global Summit in San Jose, California. It was the scene of showcasing groundbreaking innovations, expert-led sessions, and networking opportunities to drive the future of data center technology. For those who didn't get to attend or stop by our booth, here's a recap of Cadence's comprehensive solutions that enable next-generation compute technology, AI data center design, analysis, and optimization. Optimized Data Center Design and Operations As the data center community increasingly faces demands for enhanced efficiency, thermal management, sustainability, and performance optimization, data center operators, IT managers, and executives are looking for solutions to these challenges. At the Cadence booth, attendees explored the Cadence Reality Digital Twin Platform and Celsius EC Solver. These technologies are pivotal in achieving high-performance standards for AI data centers, providing advanced digital twin modeling capabilities that redefine next-generation data center design and operation. The Celsius EC Solver demonstration showed how it solves challenging thermal and electronics cooling management problems with precision and speed. CadenceCONNECT: Take the Heat Out of Your AI Data Center Cadence hosted a networking reception on October 16 titled "Take the Heat Out of Your AI Data Center." In today's AI era, managing the heat generated by high-density computing environments is more critical than ever. This reception offered insights into current and emerging data center technologies, digital twin cooling strategies that deliver energy-saving operations, and a chance to engage with industry leaders, Cadence experts, and peers to explore the latest cooling, AI, and GPU acceleration advancements. Here's a recap: Researcher, author, and entrepreneur Dr. Jon Koomey highlighted the inefficiency of data centers in his talk "The Rise of Zombie Data Centers," noting that 20-30% of their capacity is stranded and unused. He advocated for organizational changes and technological solutions like digital twins to reduce wasted energy and improve computational effectiveness as AI deployments increase. In "A New Millennium in Multiphysics System Analysis," Cadence Corporate VP Ben Gu explained the company's significant strides in multiphysics system analysis, evolving from chip simulation to a broader application of computational software for simulating various physical systems, including entire data centers. He noted that the latest Cadence venture, a digital twin platform for data center optimization, opened the opportunity to use simulation technology to optimize the efficiency of data centers. Senior Software Engineering Group Director Albert Zeng highlighted the Cadence Reality DC suite's ability to transform data center operations through simulation, emphasizing its multi-phase engine for optimal thermal performance and the integration of AI capabilities for enhanced design and management. A panel discussion titled "Turning AI Factory Blueprints into Reality at the Speed of Light" featured industry experts from NVIDIA, Norman Wright Precision Environmental and Power, NV5, Switch Data Centers, and Cadence, who explored the evolving requirements and multidimensional challenges of AI factories, emphasizing the need for collaboration across the supply chain to achieve high-performing and sustainable data centers. Watch the highlights. Transforming Designs from Chips to Data Centers The OCP Global Summit 2024 has reaffirmed its status as a pivotal event for data center professionals seeking to stay at the forefront of technological advancements. Cadence's contributions, from groundbreaking digital twin technologies to innovative cooling strategies, have shed light on the path forward for efficient, sustainable data centers. For data center professionals, IT managers, and engineers, the insights gained at this summit are invaluable in navigating the challenges and opportunities presented by the burgeoning AI era. Partnering with Arm Arm Total Design Cadence is a member of the Arm Total Design program. At an invitation-only special Arm event, Cadence's VP of Research and Development, Lokesh Korlipara, delivered a presentation focusing on data center challenges and design solutions with Arm Neoverse Compute Subsystem (CSS). The session highlighted: Efficient integration of Arm Neoverse CSS into system on chips (SoCs) with pre-integrated connectivity IP Performance analysis and verification of the Neoverse CSS integration into the SoC through Cadence's System VIP verification suite and automated testbench creation, enhancing both quality and productivity Jumpstarting designs through Cadence's collaboration with Arm for 3D-IC system planning, chiplets, and interposers Design Services readiness and global scale to support and/or deliver the most demanding Arm Neoverse CSS-based SoC design projects Cadence Supports Arm CSS in Arm Booth During the event, Cadence conducted a demo in the Arm booth that showcased the Cadence System VIP verification suite. The demo highlighted automated testbench creation and performance analysis for integrating the Arm CSS into SoCs while enhancing verification quality and productivity. Summary Cadence offers data center solutions for designing everything from the compute and networking chips to the board, racks, data centers, and campuses. Stay connected with Cadence and other industry leaders to continue exploring the innovations set to redefine the future of data centers. Learn More Cadence Joins Arm Total Design Cadence Arm-Based Solutions Cadence Reality Digital Twin Platform

Hello Folks,

Problem statement first: How does one properly setup tensorflow for running on a DSVM using a remote Docker environment? Can this be done in aml_config/*.runconfig?

I receive the following message and I would like to be able to utilize the increased speeds of the extended FMA operations.

tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA

Background: I utilize a local docker environment managed through Azure ML Workbench for initial testing and code validation so that I'm not running an expensive DSVM constantly. Once I assess that my code is to my liking, I then run it on a remote docker instance on an Azure DSVM.

I want a consistent conda environment across my compute environments, so this works out extremely well. However, I cannot figure out how to control the tensorflow build to optimize for the hardware at hand (i.e. my local docker on macOS vs. remote docker on Ubuntu DSVM)

hi,

     I save the waveform file of the oscilloscope as CSV file format.

     Now, I need to use this waveform file as the source of the low-pass filter .

     I searched and read the PSPICE help documents, and did not find any  methods. 

     How to realize it?

     Are there any reference documents or examples?

     Thanks!

Hi,

i am compiling firmware under Windows transfer the binaries and the sources to Linux to simulate/debug there. The problem is that the paths in the DWARF debug info of the .elf file are the absolute Windows paths as set by the compiler so they are useless under Linux. Is it possible to configure mappings of these paths to the Linux paths when simulating/debugging like with e.g. GDB (https://sourceware.org/gdb/current/onlinedocs/gdb/Source-Path.html#index-set-substitute_002dpath)?

thx,

Peter

This is the 19th installment of The Rationalist, my column for the Times of India.

A friend of mine was very impressed by the interview Narendra Modi granted last week to Akshay Kumar. ‘Such a charming man, such great work ethic,’ he gushed. ‘He is the kind of uncle I would want my kids to have.’ And then, in the same breath, he asked, ‘How can such a good man be such a bad prime minister?”

I don’t want to be uncharitable and suggest that Modi’s image is entirely manufactured, so let’s take the interview at face value. Let’s also grant Modi his claims about the purity of his neeyat (intentions), and reframe the question this way: when it comes to public policy, why do good intentions often lead to bad outcomes? To attempt an answer, I’ll refer to a story a friend of mine, who knows Modi well, once told me about him. 

Modi was chilling with his friends at home more than a decade ago, and told them an incident from his childhood. His mother was ill once, and the young Narendra was tending to her. The heat was enervating, so the boy went to the switchboard to switch on the fan. But there was no electricity. My friend said that as he told this story, Modi’s eyes filled with tears. Even after all these years, he was moved by the memory.

My friend used this story to make the point that Modi’s vision of the world is experiential. If he experiences something, he understands it. When he became chief minister of Gujarat, he made it his stated mission to get reliable electricity to every part of Gujarat. No doubt this was shaped by the time he flicked a switch as a young boy and the fan did not budge. Similarly, he has given importance to things like roads and cleanliness, since he would have experienced the impact of those as a young man.

My term for him, inspired by Rajat Kapoor’s 2014 film, is ‘the ankhon dekhi prime minister’. At one level, this is a good thing. He sees a problem and works for the rest of his life to solve it. But what of things he cannot experience?

The economy is a complex beast, as is society itself, and beyond a certain level, you need to grasp abstract concepts to understand how the world works. You cannot experience them. For example, spontaneous order, or the idea that society and markets, like language, cannot be centrally directed or planned. Or the positive-sum nature of things, which is the engine of our prosperity: the idea that every transaction is a win-win game, and that for one person to win, another does not have to lose. Or, indeed, respect for individual rights and free speech.

One understands abstract concepts by reading about them, understanding them, applying them to the real world. Modi is not known to be a reader, and this is not his fault. Given his background, it is a near-miracle that he has made it this far. He wasn’t born into a home with a reading culture, and did not have either the resources or the time when he was young to devote to reading. The only way he could learn about the world, thus, was by experiencing it.

There are two lessons here, one for Modi himself and others in his position, and another for everyone.

The lesson in this for Modi is a lesson for anyone who rises to such an important position, even if he is the smartest person in the world. That lesson is to have humility about the bounds of your knowledge, and to surround yourself with experts who can advise you well. Be driven by values and not confidence in your own knowledge. Gather intellectual giants around you, and stand on their shoulders.

Modi did not do this in the case of demonetisation, which he carried out against the advice of every expert he consulted. We all know the damage it caused to the economy.

The other learning from this is for all of us. How do we make sense of the world? By connecting dots. An ankhon-dekhi approach will get us very few dots, and our view of the world will be blurred and incomplete. The best way to gather more dots is reading. The more we read, the better we understand the world, and the better the decisions we take. When we can experience a thousand lives through books, why restrict ourselves to one?

A good man with noble intentions can make bad decisions with horrible consequences. The only way to hedge against this is by staying humble and reading more. So when you finish reading this piece, think of an unread book that you’d like to read today – and read it!

The India Uncut Blog © 2010 Amit Varma. All rights reserved.
Follow me on Twitter.

Read on to know about the Operating Point Parameters Summary window that gives you a one-stop view of the categorized and tabulated details on all operating point parameters in your design. This window improves your review cycle with its many benefits.(read more)

Designers have long recognized the need to analyze the reliability of ICs. Two commonly used approaches for performing reliability analysis include calculating the change in device degradation and relying on safe operating checks in circuit simulators. 

With the advent of the ever-increasing use of ICs in mission-critical applications, the need for reliable reliability analysis has become of paramount importance. Over the years, you have been using reliability analysis in Virtuoso ADE Assembler and Virtuoso ADE Explorer to measure and review aging effects, such as device characteristic degradations, model parameter changes, self-heating effects, and so on.

Reliability analysis can be performed using two modes: Spectre native and RelXpert. The reliability analysis analyzes the effect of time on circuit performance drift and predicts the reliability of designs in terms of performance. In ADE Assembler, you can run the reliability simulation for fresh test (when time is zero), stress test (to generate degradation data), and aged test (at specific intervals, such as one year, three years, or 10 years). In the stress test, extreme environmental conditions are used to stress devices before aging analysis.

The following figure shows the reliability simulation flow.

The Reliability Options form has the following four tabs: 

• Basic: Enables you to specify analysis type, aging options, start and stop time of reliability simulation, and options related to device masking, degradation ratio, and lifetime calculation. 

• Modeling: Enables you to choose the modeling type you want to use during reliability simulation. 

• Degradation: Enables you to specify the options to print device and subcircuit degradation information into a .bt0 file. 

• Output: Enables you to specify the degradation reports to be generated and methods to filter degradation results in the reports.

While the Basic and the Output tabs are used by design engineers, the Modeling and the Degradation tabs are primarily used by model developers.

Reviewing degradation reports in text or XML formats can be a tiresome exercise because degradation data can be large and can contain a large number of instances due to advanced technology nodes and post-layout simulations. For you to work effectively and interactively with these reports, the new reliability report is based on the SQLite database, which adds the benefit of improved performance and capabilities of sorting and filtering reliability data using SQLite operators.

As they say, watching this in action might help you more than reading about it, so please take a look at our Training Bytes video channel, which offers many helpful videos on how to run Reliability Analysis in Virtuoso Studio.

All the related videos are linked together in a channel so that you can easily access and watch as many as you like.

Reliability Analysis in Virtuoso Studio

Want to Learn More?

For lab instructions and a downloadable design, enroll for the online training courses of your interest on

Reliability Analysis in Virtuoso Studio vIC23.1 (Online)

 Training is also available as "Blended" or "live" class.

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About Knowledge Booster Training Bytes

Knowledge Booster Training Bytes is an online journal that relays information about Cadence Training videos, online courses, and upcoming webinars that are available in the Learning section of the Cadence Learning and Support portal. This blog category brings you direct links to these videos, courses, and other related material on a regular basis.

Niyati Singh

On behalf of the Cadence Training team

Virtuoso Studio IC23.1 ISR7 production release is now available for download.(read more)

This blog describes an efficient way to name the histories saved by the simulation runs in Virtuoso ADE Assembler.(read more)