A remarkable result in probability theory is the "three-sigma rule," which is a generic name for theorems that bound the probability that a univariate random variable will appear near the center of its distribution. This article discusses the familiar three-sigma rule for the normal distribution, a less-familiar rule for unimodal [...]

The post The three-sigma rule appeared first on The DO Loop.

In SAS, the INPUT and PUT functions are powerful functions that enable you to convert data from character type to numeric type and vice versa. They work by applying SAS formats or informats to data. You cannot fully understand the INPUT and PUT functions without understanding formats and informats in [...]

The post Understand the PUT and INPUT functions in SAS appeared first on The DO Loop.

The INPUT function and PUT function in SAS are used to apply informats and formats (respectively) to data. For both functions, you must know in advance which informat or format you want to apply. For brevity, let's consider only applying a format. To use the PUT function, you must know [...]

The post Run-time variations of the INPUT and PUT functions in SAS appeared first on The DO Loop.

A common way to visualize the sample correlations between many numeric variables is to display a heat map that shows the Pearson correlation for each pair of variables, as shown in the image to the right. The correlation is a number in the range [-1, 1], where -1 indicated perfect [...]

The post The correlogram: Visualize correlations by fitting angles appeared first on The DO Loop.

In SAS, range attribute maps enable you to specify the range of values that determine the colors used for graphical elements. There are various examples that use the GTL to define a range attribute map, but fewer examples that show how to use a range attribute map with PROC SGPLOT. [...]

The post Automate the creation of a range attribute map in SAS appeared first on The DO Loop.

Digital channels open the door to synthetic identity fraud. Luckily, artificial (AI, that is) can defeat synthetic.

The post Synthetic identity fraud: What you can’t see can hurt you appeared first on The Data Roundtable.

The evolution of service is simplicity and clarity. Build for the digital future of service today.

The post Building for the digital future of service appeared first on The Data Roundtable.

Jim Harris takes a deep dive into data lakes and how they relate to the cloud.

The post Get the scoop on data lake vs cloud appeared first on The Data Roundtable.

Backed by Iran and hated by Israel, Hezbollah chief Hassan Nasrallah is Lebanon's most powerful man. He enjoys cult status among his Shiite supporters and holds sway over the country's institutions.

Founded in 1868, Tatas have become one of largest and most diverse global conglomerates. It is a name heard in almost every home in India and tens of millions overseas.

Liam Payne, who rose to fame as a member of the boy band One Direction has died at the age of 31. The British singer fell to his death from the third-floor balcony of Hotel CasaSur Palermo in Buenos Aires, Argentina.

Think of social media, and the first name that almost immediately comes to mind is Mark Zuckerberg.

A look at how American leadership has evolved through major historical events and societal changes over the past century

An Indian-origin real estate developer and film producer has purchased 'Friends' star Matthew Perry's Los Angeles home.

US President-elect Donald Trump has named Mike Waltz, a Congressman from Florida and co-chair of the India Caucus, as the new National Security Adviser.

1. Ricky Ponting hits back at Gautam Gambhir, calls him 'prickly character'  The Times of India
2. Ricky Ponting Fires Back At Gautam Gambhir After India Coach's Press Conference Remarks  NDTV Sports
3. A fired-up Virat Kohli is Australia's worry after Ricky Ponting's 'bad move'  The Times of India
4. Gambhir a prickly character, never took dig at Kohli: Ponting  The Hindu
5. Border-Gavaskar Trophy: Why Gautam Gambhir comes across as abrasive at times  The Indian Express

1. Magnus Carlsen interview: I probably will have the most fun playing Gukesh  Hindustan Times
2. "It's Chaotic": Chess World No. 1 Magnus Carlsen Reveals Why He Does Not Play In India  NDTV Sports
3. Tata Steel Chess set for a Carlsen-Pragg opening  Hindustan Times
4. Magnus Carlsen returns to Kolkata after almost five years at Tata Steel India Rapid and Blitz 2024  ChessBase India
5. King Carlsen hails growth of Indian chess, praises Praggnanandhaa's fighting spirit  Telegraph 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

The upcoming Moto G Power 5G (2025) recently made a pit stop at the FCC where the charging speed and battery size of the phone was revealed.

The post The Moto G Power 5G (2025) was spotted at the FCC appeared first on Phandroid.

Samsung is running some Black Friday deals for its foldables like the Galaxy Z Fold 6 and Flip 6, so what are you waiting for?

The post Grab the Samsung Galaxy Z Fold 6 and Flip 6 at incredible Black Friday prices! appeared first on Phandroid.

If you’re in the market for a new Android tablet, check out these early Black Friday deals for the Samsung Galaxy Tab S10 series.

The post Check out these Samsung Galaxy Tab S10 early Black Friday deals and SAVE BIG! appeared first on Phandroid.

If you hate having your SIM locked to your carrier, then we’ll show you how to SIM unlock your iPhone 16 Pro for free!

The post How to SIM unlock the iPhone 16 Pro for FREE! 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.

The TicWatch Pro 3 Ultra packs some nifty features, in addition to impressive battery endurance.

The post Save up to 50% with the TicWatch Pro 3 Ultra! 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.

IFTTT (If This Than That), a web-based software that automates and connects over 600 online services/software raised a $24M Series C led by Salesforce. Other investors include IBM and the Chamberlain Group and Fenox Venture Capital.

The latest round brings IFTTT’s funding to $63M and it will use the funding proceeds to provide integration for enterprise and IoT services and hiring. In IFTTT’s platform, applets are code/script users need to deploy to integrate two or more services (such Google Drive’s integration with Twitter/Facebook).

Investment in IFTTT reveals that Salesforce is consolidating its presence in enterprise IoT space. It also acquired Mulesoft, an integration platform that rivals Microsoft’s BizTalk.

IBM’s investment in IFTTT is also noteworthy as the former is pushing its IBM Watson IoT platform. The following statement also shows its keen interest in IFTTT.

Other recent investments in IoT companies include $30M Series B of Armis and Myriota's $15M for its IoT satellite-based connectivity platform.

For latest IoT funding and product news, please visit our IoT news section.

EV Ultimo launches platform to assist brands, buyers, stakeholders in the Electric Vehicles ecosystem

[SAPS] Office of the Provincial Commissioner KwaZulu-Natal

[SAPS] SAPS members' continued efforts to prevent and detect crime yielded the following successes within the Joe Gqabi District as part of Operation Shanela during the week and start of the weekend .

[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.

[Daily Maverick] Office of the Chief Justice reveals Constitutional Court has been unable to sit because of unreliable water supply. This article is free to read.Sign up for free or sign in to continue reading.Unlike our competitors, we don't force you to pay to read the news but we do need your email address to make your experience better.Create your free account or sign in FAQ | Contact Us Nearly there! Create a password to finish signing up with us: You want to receive First Thing, our flagship daily newsletter. Opt

[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.

[COSATU] The Congress of South African Trade Unions (COSATU) welcomes the slight drop in the expanded unemployment rate from 42.6% in the second quarter to 41.9% in the third quarter of this year.

[spotlight] Highly effective treatments for HIV have existed since the mid-1990s. But while these treatments keep people healthy, we do not yet have a safe and scalable way to completely rid the body of the virus. In this Spotlight special briefing, Elri Voigt takes stock of where we are in the decades-long search for an HIV cure.

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

We live in a rapidly growing “digitalized world,” with an ever-increasing need for video/music streaming, gaming, AI/machine learning, etc. All of these propel demand on modern SoC design to quickly evolve the SoC by fitting more sophisti...(read more)

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.

Cadence tapes out 32G UCIe interface IP for high speed, highly efficient chiplet designs and demonstrate high data rate performance in TSMC's 3nm technology(read more)

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!

Hi everyone,

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

Thanks in Advance!

I am trying to remove the cdn_loop_breaker cells from the netlist. 
When I tried the below 2 things, genus synthesis tool removing the cdn_loop_breaker cells but while connecting the cdn_loop_breaker cell input to its proper connection, its somehow misleading the connections

Things i tried:
1.  remove_cdn_loop_breaker -instances *cdn_loop_breaker*
then i just ran remove_cdn_loop_breaker  comand without the -instances switch
2. remove_cdn_loop_breaker  
     
both of the above things are not providing the proper connections after removing the loop_breaker_cells

can anyone suggest the best possible workaround for this please?

Hi everyone. 

I'm very a new cadence user. I'm not good at using it and quite lost in finding a way to get the results. With the topic, I would like to ask you for some suggestions to improve my cadence skills.

I have some digital decision logic. Some are combinational logic, some are sequential logic that I would like to import or generate random input combination to the inputs of my decision logic to get the maximum, minimum, and average delay power dissipation and area when feeding the different input combination.

My logic has 8-bit, 16-bit, and 32-bit input. The imported data tends to be decimal numbers.

I would like to ask you:

- which tool(s) are the most appropriate to import and feed the different combination to my decision logic?

- which tool is the most appropriate to synthesis with different number of input? - I have used Genus Synthesis Solution so far. However with my skill right now I can only let Genus synthesize my Verilog code one setup at a time. I'm not sure if I there is anyway I can feed a lot of input at a time and get those results (min, max, average of delay, power dissipation and area)

- which language or scripts I should pick up to use and achieve these results?

-where can I find information to solve my problem? which information shall I look for?

Thank you so much for your time!!

Best Regards

I have a 2-dimensional input in my design - input [2:0] data_in [15:0]. After synthesis with genus, I got a netlist where the inputs are like data[15], data[14],...,data[0]. And furthermore it has definitions like input [2:0] data[15], .... So how can I define the pin locations of each of the bits for this input? Can I define data[15]'s inner bits like data[15][0]? Is it possible to define this with def files?

Is there a skill command for "Assign Layout Instance terminals", this form appears when i click on define device correspondence and Bind the devices.

Also,

Problem Statement : i have a schematic with a couple of transistor symbols and and i alos have a corresponding layout view with respective layout transistors but they all are inside a pCell(created by me) i.e layout transistor called inside a custom Pcell. Now i have multiple symbols in schematic view and a single instance(pCell) in layout view. 
Is there a way how i can bind these schematic symbols with layout symbols inside the pCell(custom)? Even if i have to use cph commands i'm fine with it. need help here.

The idea here is to establish XL connectivity between the schematic symbols and corresponding layout transistors(inside the pCell).

Thanks,

Shankar