Bring some 'oomph' to your audience with these simple content hacks

In our fast changing, increasingly digital world, building a strong customer relationship is the lynchpin to building a great business. The stakes are even higher now as global disruptions occur with alarming regularity—be it political unrest, economic meltdowns or a pandemic. A new, global study called Experience 2030: The Future [...]

4 tips for evolving your customer experience measurement was published on Customer Intelligence Blog.

No matter what your brand's level of marketing maturity is, SAS can help you move from data to insight to action with rich functionality for adaptive planning, journey activation and an embedded real-time decision engine – all fueled by powerful analytics and artificial intelligence (AI) capabilities. Let's begin with a [...]

SAS Customer Intelligence 360: Introduction to marketing data management was published on Customer Intelligence Blog.

Customer data platforms (CDPs), data management platforms (DMPs), people-based marketing, identity graphs, and more overlapping topics represent an important ingredient of any martech brainstorming session in 2020. As your brand spreads out across touchpoints — from web to mobile applications, as well as call centers, email and direct mail — [...]

SAS Customer Intelligence 360: Identity management, profiling and unified data model for hybrid marketing was published on Customer Intelligence Blog.

There's no question that we're all increasingly, and often exclusively, interacting with brands digitally. Consumers are now online through countless mechanisms – from laptops and mobile apps to AI-enabled voice assistants and sensor-based wearables. Engagement is diversifying in fascinating new ways. And when organizations can't see their customers interacting in [...]

SAS Customer Intelligence 360: Behavioral event tracking, targeting & engagement analysis was published on Customer Intelligence Blog.

The city of Heidelberg, Germany is known for its romantic cityscape, which attracts tourists from all over the world. It also has the youngest population in Germany, thanks largely to the many students at one of Europe's oldest and largest universities. Perhaps less well known is that Heidelberg is twinned [...]

The post Smart City Heidelberg: SAS Hackathon complements city's digital transformation journey appeared first on Government Data Connection.

Government employees charged with monitoring environmental compliance face a downpour of information, wading through countless reports and stacks of paperwork to accomplish their mission. To help these dedicated public servants increase productivity, agencies should consider a broader set of tools to control pollution, enforce regulations and improve compliance. Although foundational [...]

The post Time for government agencies to embed data and AI into environmental compliance appeared first on Government Data Connection.

Read the in depth Review of Temple Run 2 Gaming. Know detailed info about Temple Run 2 configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of xPUD - Firefox powered Operating System Software. Know detailed info about xPUD - Firefox powered Operating System configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of Intel NUC 11 Extreme PC Components. Know detailed info about Intel NUC 11 Extreme configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of CORSAIR DOMINATOR PLATINUM RGB First Edition DDR5 DRAM Memory Kit PC Components. Know detailed info about CORSAIR DOMINATOR PLATINUM RGB First Edition DDR5 DRAM Memory Kit configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

On September 2 (3pm UTC / 11am EDT), I'll be joining Jonathon Karelse, CEO of NorthFind Management, for an interactive "fireside chat" on the application of Behavioral Economics in demand planning. This is part of the Foresight Webinar Series, and registration is free. Since we first met at an Institute [...]

The post Behavioral economics in demand planning (webinar September 2) appeared first on The Business Forecasting Deal.

I've never been much of a fan of forecasting approaches to intermittent demand. In situations like intermittent demand (or other areas where we have little hope of reasonably accurate forecasts), my thinking is "why bother?" If we can't expect to solve the problem with forecasting, we need a different approach. [...]

The post Intermittent Demand Forecasting (new book by Boylan and Syntetos) appeared first on The Business Forecasting Deal.

When the SAS Global Forum 2020 conference was cancelled by the global COVID-19 pandemic, I felt sorry for the customers and colleagues who had spent months preparing their presentations. One presentation I especially wanted to attend was by Bucky Ransdell and Randy Tobias: "Introducing PROC SIMSYSTEM for Systematic Nonnormal Simulation". [...]

The post Introducing PROC SIMSYSTEM in SAS Viya appeared first on The DO Loop.

Having the right data analytics platform can help law enforcement solve crimes faster.

The post 5 technology considerations for law enforcement appeared first on The Data Roundtable.

The results for the Delhi University Students' Union elections will be declared on November 21, almost two months after the polls were held, according to university officials.

Japan's next prime minister, Shigeru Ishiba, says he reads three books a day and would rather do that than mingle with the ruling party colleagues who picked him as their new leader today

1. Garena Free Fire MAX redeem codes for November 13, 2024: Win bundles, new outfits, and more rewards...  Moneycontrol
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3. Garena Free Fire MAX redeem codes for November 13: Win free in-game rewards daily  The Times of India
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5. Garena Free Fire MAX November 13 redeem codes: All about Booyah Top-Up event  HT Tech

PM to visit Bihar on 13th November  PIBView Full coverage on Google News

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

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

The offer is valid across the US. Some of its international locations - the chain operates in 40 countries - also have World Kindness Day promotions planned.

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

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.

Siemens Building Technologies division announced it will acquire Enlighted Inc., a smart IoT building technology provider. The transaction is expected to close in Q3’18.

Enlighted Inc.’s core element is an advanced lighting control application. It is based on a patented, software-defined smart sensor that collects and monitors real-time occupancy, light levels, temperatures and energy usage.

The sensor can gauge temperature, light level, motion, energy, and has Bluetooth connectivity.

The Enlighted system works by collecting temperature, light and motion data via its smart sensors. A gateway device carries the information to Energy Manager, a secure browser-based interface to create profiles and adjust settings of the entire Enlighted Advanced Lighting Control System. The Energy manager operates as an analytics device.

The whole system consists of multi-function sensors, distributed computing, a network, and software applications run by Enlighted Inc.

Enlighted Inc.’s main target market is commercial real estate. Key use cases of its intelligent Lighting Control System are energy efficiency, controlling heating, ventilation and air conditioning, and building utilization reports.

Use the Postscapes 'Connected Products Framework' to understand the smart home and buildings eco-system.

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

[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.

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

[allAfrica]

[allAfrica]

[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.

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

[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.

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.

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.

Today's high-performance computing systems often require the designer to instantiate multiple CPU or DSP cores in their subsystem. However, the performance gained by using multiple CPUs comes with additional programming complexity, especially when accessing shared memory data structures and hardware peripherals. CPU cores need to access shared data in an atomic fashion in a multi-core environment. Locking is the most basic requirement for data sharing. A core takes the lock, accesses the shared data structure, and releases the lock. While one core has the lock, other cores are disallowed from accessing the same data structure. Typically, locking is implemented using an atomic read-modify-write bus transaction on a variable allocated in an uncached memory.

This blog shares the AXI4 locking mechanism when implementing an Xtensa LX-based multi-core system on a Xilinx FPGA platform. It uses a dual-core design mapped to a KC705 platform as an example.

Exclusive Access to Accomplish Locking

The Xtensa AXI4 manager provides atomic access using the AXI4 atomic access mechanism. While Xtensa's AXI manager interface generates an exclusive transaction, the subordinate's interface is also expected to support exclusive access, i.e., AXI monitoring. Xilinx BRAM controller's AXI subordinate interface does not support exclusive access, i.e., AXI monitoring: AXI Feature Adoption in Xilinx FPGAs.

Leveraging Xtensa AXI4 Subordinate Exclusive Access

The Xtensa LX AXI subordinate interface supports exclusive access. One approach is to utilize this support and allocate locks in one of the core's local data memories. Ensure that the number of external exclusive managers is configured, typically to the number of cores (Figure 1).

Figure 1

Note that the Xtensa NX AXI subordinate interface does not support exclusive access. For an Xtensa NX design, shared memory with AXI monitoring is required.

In Figure 2, the AXI_crossbar#2 (block in green) routes core#0's manager AXI access (blue connection) to both core's local memories. Core#1's manager AXI (yellow connection) can also access both core's local memories. Locks can be allocated in either core's local data memory.

In-Bound Access on Subordinate Interface

On inbound access, the Xtensa AXI subordinate interface expects a local memory address, i.e., an external entity needs to present the same address as the core would use to access local memory in its 4GB address space. AXI address remap IP (block in pink) translates the AXI system address to each core's local address. For example, assuming locks are allocated in core#0's local memory, core#1 generates an AXI exclusive to access a lock allocated in core#0's local memory (yellow connection). AXI_crossbar#2 forwards transaction to M03_AXI port (green connection). AXI_address_remap#1 translates the AXI system address to the local memory address before presenting it to core#0's AXI subordinate interface (pink connection).

It is possible to configure cores with disjoint local data memory addresses and avoid the need for an address remap IP block. But then it will be a heterogeneous multi-core design with a multi-image build. An address remap IP is required to keep things simple, i.e., a homogeneous multi-core with a single image build. A single image uses a single memory map. Therefore, both cores must have the same view of a lock, i.e., the lock's AXI bus address must be the same for both.

Figure 2

AXI ID Width

Note Xtensa AXI manager interface ID width=4 bits. Xtensa's AXI subordinate interface ID width=12 bits. So, you must configure AXI crossbar#2 and AXI address remap AXI ID width higher than 4. AXI IDs on a manager port are not globally defined; thus, an AXI crossbar with multiple manager ports will internally prefix the manager port index to the ID and provide this concatenated ID to the subordinate device. On return of the transaction to its manager port of origin, this ID prefix will be used to locate the manager port, and the prefix will be truncated. Therefore, the subordinate port ID is wider in bits than the manager port ID. Figure 3 shows the Xilinx crossbar IP AXI ID width configuration.

Figure 3

Software Tools Support

Cadence tools provide a way to place locks at a specific location. For more details, please refer to Cadence's Linker Support Packages (LSP) Reference Manual for Xtensa SDK. .xtos.lock(green) resides in core#0's local memory and holds user-defined and C library locks. The lock segment memory attribute is defined as shared inner (cyan) so that L32EX and S32EX instructions generate an exclusive transaction on an AXI bus. See Figure 4. The stack and per-core Xtos and C library contexts are allocated in local data memory (yellow).

…………..LSP memory map………….
BEGIN dram0
0x40000000: dataRam : dram0 : 0x8000 : writable ;
dram0_0 : C : 0x40000400 - 0x40007fff : STACK : .dram0.rodata .clib.percpu.data .rtos.percpu.data .dram0.data .clib.percpu.bss .rtos.percpu.bss .dram0.bss;
END dram0
…………………
BEGIN sysViewDataRam0
0xA0100000: system : sysViewDataRam0 : 0x8000 : writable, uncached, shared_inner;
lockRam_0 : C : 0xA0100000 - 0xA01003ff : .xtos.lock;
END sysViewDataRam0
…………..

Figure 4

Please visit the Cadence support site for more information on emulating Xtensa cores on FPGAs.

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!

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

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

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

Thank you for your help!

Hi everyone,

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

Thanks in Advance!

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?

We are currently setting up the Tempus flow and have ran into some mismatched data regarding ECO and timing reports. I generated a timing report before running ECO and saw six total setup violations. When running opt_signoff -setup, the initial setup summary that was printed in the shell only showed one violation. I can see that violation from the initial setup summary in my pre-ECO timing report and it is not the worst path. Upon further investigation, I forced the tool to try to fix setup on one of the other five violations from the timing report using the opt_signoff_select_setup_endpoints attribute and the tool said that the endpoint had positive slack and would be ignored.

Has anyone experienced something like this before?

Hi all, while saving design, there is an error saying a net has tid problem. However the design is saved. Does anybody know how to resolve the Tid problem?

With digital implementation rapidly advancing, how do you think iOS and Android platforms will continue to evolve in industries like healthcare or education? The integration of mobile technology is already revolutionizing these fields, and it would be interesting to discuss where this could lead and what new opportunities might emerge.

Hi! I've made some 1-point waveform "markers" that I want to overlay in my plots to aid visualization (with the added advantage, w.r.t. normal Viva markers, that they update location automatically upon refreshing simulation data).

For example, the plot below shows an spectrum along with two of these markers, which I create with the function "singlePointWave", and the Assembler output definitions also as shown below.

The problem is: as currently created and defined, Assembler is unable to plot these elements. I can send their expressions to the calculator and plotting works from there, BUT ONLY after first enabling the "Allow Any Units" in the target Viva subwindow.

Thus, I suspect Assembler is failing to plot my markers because they "lack" other information like axes units and so on. How could I add whatever is missing, so that these markers can plot automatically from Assembler?

Thanks in advance for any help!

Jorge.

P.S. I also don't know why, but nothing works without those "ymax()" in the output definitions--I suspect they are somehow converting the arguments to the right data type expected by singlePointWave(). Ideas how to fix that are also welcome! ^^

procedure( singlePointWave(xVal yVal)
    let( (xVect yVect wave)
        xVect = drCreateVec('double list(xVal));
        yVect = drCreateVec('double list(yVal));
        wave = drCreateWaveform(xVect yVect);
    );
);

Hi,all

  I want to remove some Tests form adexl automatically,there have any function to achieve that?