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

Learn why integrating EHR data with pharmacy and claims data improves patient care.

The post Closing data gaps to promote integrated health care appeared first on The Data Roundtable.

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.

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 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.

1. Google Chrome on iPhones gets new features with Drive, Maps integration  Business Standard
2. Stop Using Chrome On Your iPhone, Warns Apple—Millions Of Users Must Now Decide  Forbes
3. 4 new Chrome improvements for iOS  The Keyword
4. Chrome on iOS now lets you search using images and text at the same time  TechCrunch
5. Google rolls out new features in Chrome for iPhone users  Moneycontrol

1. Battered Reliance Shares To Make A Comeback? This Analyst Sees 29% Upside Ahead  Benzinga India
2. Reliance Industries shares may see 30% upside according to CLSA, who cites this key trigger  CNBCTV18
3. RIL shares are down 20% from record high, oversold on charts; here's what analysts say  Business Today
4. Six of India’s top 10 most valuable firms shed Rs 1.55 lakh crore in market value  Moneycontrol
5. Reliance Industries Share Price Today on 13-11-2024: Reliance Industries share price are down by -0.63%, Nifty down by -0.8%  Mint

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

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The video features models dressed in the latest fashion, strutting like mannequins on a moving runway outside the designer store ITIB.

Smart Lock Company LockState raised $5.8M Series A in new investment to fund its aggressive sales and marketing and partner development plan. The company previously raised $740K seed round and $1M in a round led by angel investors. The lead investor in latest round was Iron Gate Capital. Other investors include Kozo Keikaku Engineering Inc, Nelnet and Service Provider Capital.

The company’s Wi-Fi-enabled RemoteLock is used by 1000s of Airbnb and other vacation rental hosts. It helps hosts remotely provide access to guests. Locking/unlocking codes can be generated via a host’s computer or smartphone.

RemoteLock’s prices start at $299 which is its algorithmic ResortLock. The most pricey lock by LockState is its ‘RemoteLock 7i Black WiFi Commercial Smart Lock’ which costs $479.

Another core product of LockState is its cloud-based remote access platform for internet-enabled locks. It implies users can remotely manage their (internet-enabled) locks via LockState’s cloud platform.

Unlike smartphones and watches, customers don’t look forward to upgrading their smart locks or buying one when new models are launched. Thus, smart lock companies offset this disadvantage by partnering with property management and short-term rental companies to get new customers.

LockState has partnered with vacation rental brands like Airbnb, HomeAway, and other listing partners to automate guest access.

Igloohome a Singapore-based smart lock company also raised an investment of $4M in April this year.

[allAfrica]

[DA] It is a national embarrassment that the inability of the City of Johannesburg to supply water to its residents, business and public sector offices, has now led to the shutdown of operations at the Constitutional Court, on Constitution Hill in Braamfontein.

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.

Xcelium Simulator has been in the industry for years and is the leading high-performance simulation platform. As designs are getting more and more complex and verification is taking longer than ever, the need of the hour is plug-and-play apps that ar...(read more)

Hearing is one of the most essential senses for engaging with the world. It enables us to converse, appreciate music, and remain alert to our surroundings. Hearing loss is a prevalent issue affecting millions of individuals globally and disconnecting them from a world where sound is vital to others and the environment. The World Health Organization (WHO) reports that over 5% of the global population requires hearing rehabilitation, a striking statistic highlighting this issue's pervasive nature. Technology has transformed audiology, evolving from simple ear trumpets to sophisticated modern hearing aids. This advancement began with the invention of the transistor, paving the way for devices that are fully wearable inside or behind the ear. Although hearing aids have been available for many years, historically, access to these critical devices has been insufficient, resulting in numerous individuals lacking the necessary support. However, recent advances in hearing aid technology promise improved acoustic experiences, employing modern techniques like binaural processing and neural networks. These innovations demand sophisticated architecture to balance high memory needs with low power consumption in a user-friendly design. Cadence is at the forefront of this technological evolution, offering tools and IP solutions that enhance the accessibility, efficiency, and impact of hearing aids, paving the way for a more inclusive future. This blog explores how Cadence's advanced DSPs are transforming hearing aid design and making them more accessible, efficient, and impactful. Hearing Aids: A Testament to Human Ingenuity The transition from analo g to digital technology in the late 20th century further transformed hearing aids, offering superior sound quality, customization, and the ability to connect to various electronic devices, thus enhancing the user experience markedly. Today's hearing aids are highly effective, versatile, and nearly invisible, a significant advancement from early attempts to address hearing loss. They also feature advanced noise cancellation and connectivity options, allowing users to integrate seamlessly into the digital world. This progression not only highlights the industry's commitment to improving user experience and accessibility but also offers a glimpse into a future where hearing loss is no longer a barrier. Challenges Despite advancements and sophistication, there are several challenges related to hearing aid design and adoption. Users demand smaller, more discreet devices that don't sacrifice performance. While the shift towards sleeker designs is aesthetically pleasing, it introduces substantial complexities in product design. Designers face the challenges of integrating essential components, such as batteries and peripherals, into increasingly compact spaces. Power consumption remains a critical concern, as these devices must remain operational throughout the day. Leveraging neural networks to enhance the signal-to-noise ratio (SNR) for better quality demands additional memory capacity. Consequently, there is a pressing need for flexible, low-power architectures that incorporate all necessary memory and peripherals without compromising the device’s compact size. Adopting AI for adjusting hearing aid volume to fit an individual's specific auditory requirements is a significant challenge and demands more memory and effort. Besides this, reliability and cost are significant challenges for manufacturers. Cadence's Role in Transforming Hearing Aids In hearing aid development, the capacity to evaluate the energy efficiency of SoCs across different frequencies in real time is crucial. These applications demand cohesive, energy-efficient solutions that can uphold high performance. The Cadence Tensilica HiFi and Fusion F1 DSP family emphasize minimal power usage while providing robust performance, ideally suited for a wide range of audio and voice applications. The Cadence Tensilica HiFi DSP family, a high-performance audio technology with AI acceleration and advanced DSP capability, offers feature-rich audio, speech, and imaging for wearables, automotive, home entertainment, digital assistants, and ASR. The Tensilica HiFi DSP family accelerates innovation with its comprehensive instruction set and supports fixed- and floating-point data types. Simplifying software development, it offers C/C++ programming, an auto-vectorizing compiler, and a rich DSP software library through the Cadence Tensilica Xplorer development environment. With the flexibility to customize and enhance performance through additional instructions and better I/O bandwidth, the Tensilica HiFi and Fusion DSP families offer a robust, low-energy audio solution compatible across an expansive software ecosystem for various applications and devices. Conclusion Technological advancements are driving hearing aid evolution; the future of hearing aids lies in further miniaturization and functionality enhancement. Cadence's ongoing innovations aim to improve signal processing and noise reduction, even in challenging environments. The integration of neural networks promises more apparent sound transmission and greater adaptability. Cadence is working on improving how these devices process signals and reduce noise and has initiated a collaborative venture with distinguished entities like GlobalFoundries (GF), Hoerzentrum Oldenburg gGmbH, and Leibniz University Hannover. This collaboration has borne fruit in the form of the industry's first binaural hearing aid system-on-chip (SoC) prototype, the Smart Hearing Aid Processor ( SmartHeAP ). Learn More Cadence, GlobalFoundries, Hoerzentrum Oldenburg and Leibniz University Hannover Collaborate to Advance Hearing Aid Technology Cadence Extends Battery Life and Improves User Experience for Next-Generation Hearables, Wearables and Always-On Devices Advancing the Future of Hearing Aids with Cadence Bluetooth LE Audio, Hearing Aids, and Mindtree

An increasing number of embedded designs are multi-core systems. At the pre-silicon stage, customers use a simulation platform for architectural exploration and software development. Architects want to quantify the impact of the number of cores, local memory size, system memory latency, and interconnect bandwidth. Software teams wish to have a practical development platform that is not excruciatingly slow. This blog shares a recipe for simulating Cadence DSPs in a multi-core design as separate x86 processes. The purpose is to reduce simulation time for customers with simple multi-core models where cores interact only through shared memory. It uses a Vision Q8 multi-core design to share details of the XTSC (Xtensa SystemC) model, software application, commands, and debugging. Note the details shared are for a simulation run on an Ubuntu Linux machine, Xtensa tools version RI-2023.11, and core configuration XRC_Vision_Q8_AODP. Complex vs. Simple Model A complex model (Figure 1) is one in which one core accesses another core's local memory, or there are inter-core interrupts. Simulation runs as a single x86 process. Figure 1 A simple model (Figure 2) is one in which cores interact only through shared memory. Shared memory is a file on the Linux host. Figure 2 Multiple x86 Process – Simple Model As depicted in Figure 3, each core is simulated using a separate x86 process. Cores use barriers and locks placed in shared memory for synchronization and data sharing. Locks are placed in un-cached memory that support exclusive subordinate access. The XTSC memory component, xtsc_memory , supports exclusive subordinate access. Cadence software tools provide a way to define memory regions as cached or uncached. For more details, please refer to Cadence's Linker Support Packages (LSP) Reference Manual for Xtensa SDK . Figure 3 Demo Application A demo application performs a 128x128 matrix multiplication. Work is divided so that each of the 32 cores computes four rows of the 128x128 result matrix. Cores use barriers to synchronize. Cadence tools provide APIs for synchronization and locking. Please refer to Cadence's System Software Reference Manual for more details. Note without a higher-level lock, prints from all cores will get mixed up. Therefore, in the demo application, only core#0 prints. SystemC Simulation The following sample command runs the 32-core simulation in such a way that each core is a separate x86 process. It runs a matrix multiplication application in cycle-accurate mode with logging off. >>for (( N=0; N >xtsc-run -define=NumCores=32 -define=N=0 -define=LOGGING=0 -define=TURBO=0 --xxdebug=sync -i=coreNN.inc -sc_main=sc_main.cpp -no_sim Modify the sc_main.cpp generated for core#0 to create a generic sc_main.cpp to build a single simulation executable for all cores. The Xtensa SDK includes Makefile targets to build custom simulations. By default, the simulation runs in cycle-accurate mode. Fast functional (Turbo) mode provides additional improvement over cycle-accurate mode. Note that the fast functional mode has an initialization phase, so gains are visible only when running an application with longer run times. Simulation Wall Time The table captures simulation wall time improvements. Note that these are illustrative wall time numbers. Actual wall time numbers and improvements will depend on your host machine's performance and your application. Simulation Type Wall Time Comments Single process cycle accurate mode 17500 seconds Multiple x86 processes cycle accurate mode 1385 seconds 12X faster than single process Multiple x86 processes turbo mode 415 seconds 3X faster than cycle accurate mode Debugging Attaching a debugger to each of the individual x86 core simulation processes is possible. Synchronous stop/resume and core-specific breakpoints are also supported. Configure the Xplorer launch configuration and attach it to the running simulation processes as follows (Figure 5) Figure 5 Figure 6 shows 32 debug contexts. Figure 6 As shown, using Xtensa SDK, you can create a multi-core simulation that functions as a practical software development platform. Please visit the Cadence support site for information on building and simulating multi-core Xtensa systems.

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!

Cadence_SPB_17.4-2019 + Matlab R2019a

请参考本文档中的步骤进行操作

1，打开BJT_AMP.opj

2，设置Matlab路径

3，打开BJT_AMP_SLPS.slx

4，打开后，设置PSpiceBlock，出现或CEFSimpleUI.exe停止工作

5，添加模块

6，相同

7，打开pspsim.slx

8，相同

9，打开C： Cadence Cadence_SPB_17.4-2019 tools bin

orCEFSimpleUI.exe和orCEFSimple.exe

10，相同

我想问一下如何解决，非常感谢！

I want to use PSpice model (download from TI) in Virtuoso , but it can not work. Please help me to check the error message, Thanks

ADE-> Setup-> simulation files->Pspice  Files  /TPS628502-Q1_TRANS.LIB

Parse error before token ']' in expression '[[STEADY_STATE]*0.6]'. If '[[STEADY_STATE]*0.6]'  is a spice expression, quotes are required for the expression.

ERROR(SFE-46): An instance of 'TPS628502-Q1_TRANS'  can have at most 8 terminals (but has 9).

*****************************************************************************
.SUBCKT TPS628502-Q1_TRANS COMP_FSET EN FB GND PG SW SYNC_MODE VIN
+ PARAMS: STEADY_STATE=0
V_U9_V45 U9_N16725824 0 5
E_U9_ABM22 U9_N16725392 0 VALUE { V(FREQ)*1e-12 }
X_U9_U161 U9_N16849713 U9_N16846056 one_shot PARAMS: T=20

Hello all,

I have run a simulation with a lot of instnaces extraction and the psf.trn is >= 200 Gb, I tried to load it with simvision and it just breaks.

I would like to ask if there is a way to open this file, e.g. if I could read only some time window e.g. from 10us -> 15us.

getVersion(t)
"sub-version  ICADVM20.1-64b.500.34 "

XCELIUMMAIN23.03.001

thank you in advance

I am running simulation in gui mode using Indago and every time there is UVM_ERROR occur simulation stops. I have to resume it manually. is there any way to disable this feature. 

Hi *,

I am simulating a 32kHz high Q crystal oscillator with a pulse shaping circuit. I set up a PSS analysis using the Shooting Newton engine. I set a beat frequency of 32k and used the crystal output and ground as reference nodes. After the initial transient the amplitude growth was already pretty much settled such that the shooting iterations could continue the job.

My problem is: In 5...10% of my PVT runs the simulator detects a frequency divider in the initial transient simulation. The output log says:

Frequency divided by 3 at node <xxx>

The Estimated oscillating frequency from Tstab Tran is = 11.0193 kHz .

However, the mentioned node is only part of the control logic and is always constant (but it has some ripples and glitches which are all less than 30uV). These glitches spoil my fundamental frequency (11kHz instead of 32kHz). Sometimes the simulator detects a frequency division by 2 or 3 and the mentioned node <xxx> is different depending on PVT - but the node is always a genuine high or low signal inside my control logic.

How can I tell the simulator that there is no frequency divider and it should only observe the given node pair in the PSS analysis setup to estimate the fundamental frequency? I have tried the following workarounds but none of them worked reliably:

- extended/reduced the initial transient simulation time

- decreased accuracy

- preset override with Euler integration method for the initial transient to damp glitches

- tried different initial conditions

- specified various oscillator nodes in the analysis setup form

By the way, I am using Spectre X (version 21.1.0.389.ISR8) with CX accuracy.

Thanks for your support and best regards

Stephan

In this post, we will learn about the most important parameters for the analog simulators that affect the accuracy of the simulation results. We will also understand how each parameter limits the accuracy of the measurements for the DC and transient analyses.(read more)

This blog describes the new capabilities in Spectre 21.1 ISR2 through which it provides support to the Voltus-XFi Custom Power Integrity Solution.(read more)

London has been named fDi’s inaugural Fintech Location of the Future for 2019/20, followed by Singapore and Belfast. 

Poor infrastructure and political instability deter tourism, but small and manageable steps to avoid chaos and promote hospitality can work wonders.

Kenya’s cabinet secretary for the national treasury and planning, Ukur Yatani, discusses the country’s agenda of fiscal reforms and the importance of constructing an east-west Africa highway.

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Financial incentives from two different cities persuaded US grocery chain The Fresh Market to stay headquartered in its home state of North Carolina.

Investors in France will face greater scrutiny under extended legislation.