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Podcast EP184: The History and Industry-Wide Impact of TSMC OIP with Dan Kochpatcharin

Podcast EP184: The History and Industry-Wide Impact of TSMC OIP with Dan Kochpatcharin
by Daniel Nenni on 09-27-2023 at 2:00 pm

Dan is joined by Dan Kochpatcharin, Dan joined TSMC in 2007. Prior to his current role heading up the Design Infrastructure Management Division, Dan led the Japan customer strategy team, the technical marketing and support team for the EMEA region in Amsterdam and was a part of the team leading the formation of the TSMC Open Innovation Platform. Prior to TSMC, Dan worked at Chartered Semiconductor both in the US and Singapore and LSI Logic.

The history of TSMC ecosystem collaboration is reviewed, starting with the first reference flow work in 2001. TSMC’s OIP Ecosystem has been evolving for the past 15 years and Dan provides an overview of the activities and impact of this work. Ecosystem-wide enablement of 3DIC design is also discussed with a review of the TSMC 3DFabric Alliance and 3Dblox.

The views, thoughts, and opinions expressed in these podcasts belong solely to the speaker, and not to the speaker’s employer, organization, committee or any other group or individual.


Version Control, Data and Tool Integration, Collaboration

Version Control, Data and Tool Integration, Collaboration
by Daniel Payne on 09-27-2023 at 10:00 am

SoC Complexity min

As a follow up from my #60DAC visit with Simon Rance of Keysight I was invited to their recent webinar, Unveiling the Secrets to Proper Version Control, Seamless Data and Tool Integration, and Effective Collaboration. Karim Khalfan, Director of Solutions Engineering, Data & IP Management was the webinar presenter.

Modern SoC devices can contain hundreds of semiconductor IP blocks that could contain subsystems for: CPU, GPU, Security, Memory, Interconnect, NoC, and IO. Keeping track of such a complex system of subsystems requires automation.

SoC Complexity

Version Control

The goals of a version control tool for SoC design are to capture objects used in a release, ensure data security, resolve conflicts from multi-user check-ins, maintain design handoffs using labels, and being able to revert to a stable version of the system. Access controls define which engineers can read or modify the system, something that is required for military projects through ITAR compliance. Authorized engineers can check out IP like hardware or software, work on a branch, resolve conflicts with other team members, then merge changes when ready by checking in or committing

Designers with version control can update specific objects, go back in time to revert previous versions and use labels to assist in communicating with their team what each update is about. Modern version control tools should allow both command line and GUI modes to suite the style of each project.

Reuse and Traceability

The first diagram showed just how much IP that it can take to design a system, so being able to re-use trusted IP from internal or external sources is required, along with being able to trace where each IP block came from along with it’s version history. Industries like aerospace and automotive have requirements to archive their designs over a long period of time, so having thorough documentation is key to understanding the BOM.

IP developers need to know who who is using each IP block, and IP users need to be informed when any changes or updates have been made to an IP block. The legal department needs to know how each IP bock is licensed, and how many of each block is being actively used in designs. The Design Data Management tool from Keysight is called SOS. A traceability report should show where each IP block is being used across a global scale, by version, and by geography. If two versions of the same IP are referenced in the same project, then a conflict should be detected and reported.

IP by Geography

Storage Optimization

SoC design sizes continue to increase in size, so how the data is stored and accessed becomes an issue.

Design # of Files File Size
12 Bit ADC 25K 150GB
Mixed Signal Sensor 100K 250GB
PDK 300K 800GB
Processor 500K 1,500GB

With a traditional storage approach there is a physical copy of the data per user, so for a team of five engineers there would be five copies of the data. Each new engineer grows the disk space linearly, requiring more network storage.

The Keysight SOS approach instead uses a centralized work area, then design files in a users work area are symbolic links to a cache, except for files to be edited. This creates an optimized use of network storage, saving on disk space for the team. Creating a new user work area is quite fast.

SOS storage

Team & Site Collaboration

Without remote sharing of IP blocks, your engineering team may be working on the wrong version of data, wasting time trying to locate the golden data, using stale data that is out of sync, or even handing off data to another geography that is out of date. Keysight recommends using labels as tags to communicate between team members, and also using tags to represent milestones in the IC design process. In the following diagram there’s a mixed-signal design flow with tags and labels being used to ensure that the correct versions are being used by each engineer.

Mixed-signal design flow using tags and labels

Once the design methodology is established, then each geography can work concurrently sharing data through the repository and cache system. SOS supports automatic synching data across sites, so there is fast access to data at each remote site. Even remote updates are performed quickly just like at the primary site, as the traffic of data is reduced, and this approach also works in cloud-based EDA tool flows. Remote design centers and cloud users are both supported, as the data management is built in.

Integration

Over many years the Keysight SOS tool has been integrated with the most popular EDA software vendor flows.

  • MathWorks
  • Siemens
  • Synopsys
  • Keysight
  • Cadence
  • Silvaco
  • Empyrean

These are all native integrations, so the data management and version control are consistent across projects, groups and geographies. The SOS tool runs under Windows or Linux, has a web interface, and can also be run from the command line. Here’s what the SOS interface looks like to a Cadence Virtuoso user:

SOS commands in Cadence Virtuoso

Summary

Having an integrated data management tool within your favorite EDA flow will help your design team’s productivity, as it automatically synchs your data around the world to ensure that all members are accessing the correct IP blocks. Using a tagging methodology to promote data once it gets completed will communicate to everyone on a team what state each block is in. All of your IP reuse will now have traceability to more easily audit data.

Version control has gone beyond just the simple check-in, checkout and update cycles, as advanced flows need to also support variations of experiments or branches. The archived webinar is online now here.

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WEBINAR: Emulation and Prototyping in the age of AI

WEBINAR: Emulation and Prototyping in the age of AI
by Daniel Nenni on 09-27-2023 at 8:00 am

mimic 128

Artificial Intelligence is now the primary driver of leading edge semiconductor technology and that means performance is at a premium and time to market will be measured in billions of dollars of revenue. Emulation and Prototyping have never been more important and we are seeing some amazing technology breakthroughs including a unified platform from Corigine.

How does an innovative and unified platform for Prototyping and Emulation deliver never seen speeds, truly fast enough for system software development?

How is Debug made possible with powerful capabilities to shorten validation times by orders of magnitude?

Is Push-Button automation for real? And how can scalability go from 1 to 128 FPGA’s on the fly?

To answer these questions, please join the Corigine coming up webinar. We will showcase the new MimicPro-2 platform architected and designed from the ground up by the pioneers of Emulation and Prototyping.

LIVE WEBINAR: Emulation and Prototyping in the age of AI
October 18, 9:00am PDT

The complexity of hardware and software content increases the need of faster emulation and prototyping capacity to achieve the hardware verification and software development goals. Identifying the best balance of emulation and prototyping hardware capacity for SoC design teams is always challenging. This is why Corigine made the best effort to determine the upfront unified prototyping and emulation platform.

Corigine’s team hailing from the days of Quickturn and developing generations of Emulation and Prototyping at the big EDA companies has architected a unified new platform. The new platform breaks barriers in a space that has not been keeping pace with the needs of AI, Processors and Communications SoCs that need software running at the system performance levels…pre-silicon. And as the shift-left push shortens R&D cycles, enormous innovations in debug are necessary, with the kind of backdoor access and system view transparency that is near-impossible with legacy emulation and prototyping platforms. A new Corigine platform will be unveiled in this webinar to showcase and demo what is achievable

Why attend?

In this webinar, you will gain insights on:

  • What new levels are achievable for software and hardware teams for
    • Pre-silicon emulation performance
    • Debug capabilities as never seen before
    • Multi-user accessibility and granularity
  • What is next on the prototyping and emulation roadmap
LIVE WEBINAR: Emulation and Prototyping in the age of AI
October 18, 9:00am PDT
Speakers:

Ali Khan
The VP Business and Product Development at Corigine. He has over 25 years of experience building startups and running businesses, with particular expertise in the semiconductor sector. Before joining Corigine, Ali was Director of Product Management at Marvell, Co-Founder of Nexsi System, and Server NIC Product Manager at 3Com. Ali obtained a bachelor’s degree in Electrical Engineering from UT Austin and MBA from Indiana University.

Mike Shei
The VP Engineering at Corigine. Mike has over 30 years of experience on emulation/prototyping tools.

About Corigine
Corigine is a leading supplier of FPGA prototyping cards and systems to shift left R&D schedules. Corigine delivers EDA tools, IPs and networking products. Corigine has worldwide R&D centers and offices in US, London, South Africa, and China. https://www.corigine.com/

Also Read:

Speeding up Chiplet-Based Design Through Hardware Emulation

Bringing Prototyping to the Desktop

A Next-Generation Prototyping System for ASIC and Pre-Silicon Software Development


Power Supply Induced Jitter on Clocks: Risks, Mitigation, and the Importance of Accurate Verification

Power Supply Induced Jitter on Clocks: Risks, Mitigation, and the Importance of Accurate Verification
by Daniel Nenni on 09-27-2023 at 6:00 am

Jitter Analysis

In the realm of digital systems, clocks play a crucial role in synchronizing various components and ensuring smooth flow of logic propagation. However, the accuracy of clocks can be significantly affected by power supply induced jitter. Jitter refers to the deviation in the timing of clock signals with PDN noise compared to ideal periodic timing. This essay explores the risks associated with power supply induced jitter on clocks, strategies to mitigate its impact, and the crucial role of accurate verification in maintaining reliable clock performance.

Infinisim JitterEdge is a specialized jitter analytics solution, designed to compute power supply induced jitter of clock domains containing millions of gates at SPICE accuracy. It computes both period and cycle-to-cycle jitter at all clock nets, for all transitions using large milli-second power-supply noise profiles. Customers use Infinisim jitter analysis during physical design iterations and before final tape-out to ensure timing closure.

Understanding Power Supply Induced Jitter

Power supply induced jitter occurs when fluctuations or noise in the power supply voltage affect the timing of a clock signal. In digital systems, clock signals are typically generated by phase-locked loops (PLLs) or delay-locked loops (DLLs). PLL jitter is added to the PDN jitter to compute total clock jitter.

Risks of Power Supply Induced Jitter

  1. Timing Errors: The primary risk associated with power supply induced jitter is the introduction of timing errors. These errors can lead to setup and hold violations resulting in synchronization errors between different components
  2. Increased Bit Error Rates (BER): Jitter-induced timing errors can result in data transmission issues, leading to a higher BER in communication channels. This can degrade the overall system’s reliability and performance.
  3. Reduced Signal Integrity: Jitter can cause signal integrity problems, leading to crosstalk, data corruption, and other noise-related issues, especially in high-speed digital systems.
  4. Frequency Synthesizer Instability: In systems that rely on frequency synthesizers for clock generation, power supply induced jitter can cause the synthesizer to become unstable, leading to unpredictable system behavior.

Mitigating Power Supply Induced Jitter

To minimize the impact of power supply induced jitter on clocks, several mitigation strategies can be employed:

  1. Quality Power Supply Design: Implementing a robust and well-designed power supply system is crucial. This includes the use of decoupling capacitors, voltage regulators, and power planes to reduce noise and fluctuations in the supply voltage.
  2. Filtering and Isolation: Incorporate filtering mechanisms to remove high-frequency noise from the power supply. Additionally, isolate sensitive clock generation circuits from noisy power sources to limit the propagation of jitter.
  3. Clock Buffering and Distribution: Utilize clock buffers to distribute the clock signal efficiently and accurately. Proper buffering helps to isolate the clock signal from the original source, reducing the impact of jitter.
  4. Clock Synchronization Techniques: Implement clock synchronization techniques that enable multiple components to share a common reference clock, mitigating potential timing discrepancies.
  5. Minimize Load and Crosstalk: Reduce the capacitive load on clock distribution networks and minimize crosstalk between clock and data signals to maintain signal integrity.

Importance of Accurate Verification

Accurate verification of power supply induced jitter is essential for several reasons:

  1. System Reliability: Accurate verification ensures that the system meets timing requirements, reducing the risk of errors and malfunctions caused by jitter-induced timing variations.
  2. Performance Optimization: By understanding the extent of jitter in the system, designers can optimize clock generation and distribution, maximizing performance without compromising reliability.
  3. Compliance with Standards: Many industries and applications have specific timing requirements, such as in telecommunications or safety-critical systems. Accurate verification ensures compliance with these standards.
  4. Cost and Time Savings: Early identification and mitigation of power supply induced jitter during the verification process save time and resources, preventing potential issues during product deployment.

Conclusion

Power supply induced jitter on clocks poses significant risks to the accurate operation of digital systems. Mitigation strategies, including quality power supply design, filtering, and proper clock distribution, are essential for reducing jitter’s impact. Accurate verification of power supply induced jitter is crucial to maintaining system reliability, optimizing performance, and ensuring compliance with industry standards. By understanding and addressing this challenge, designers can create more robust and dependable digital systems capable of meeting the demands of modern technology.

Characterization is a common technique used in the analysis of clock jitter and involves measuring and quantifying the variations in a clock signal’s timing. Characterization is often used to describe the process of measuring and analyzing the behavior of a signal or component to understand its performance characteristics. In the context of clock jitter, characterization-based tools measure the statistical distribution of jitter values, determine key metrics such as RMS jitter and peak-to-peak jitter, and analyzing how different factors in the design contribute to jitter.

For designs at 7nm and below nodes, where a sub-pico-second level of jitter needs to be identified, a more accurate approach is needed. Running a full circuit simulation at the transistor-level along with parasitic interconnect can provide SPICE accurate Jitter analysis and help identify sources of jitter and their impact. Infinisim’s ClockEdge’s jitter capability provides the accuracy needed to model clock jitter and its effects.

If you have questions feel free to contact the clock experts at Infinisim here: https://infinisim.com/contact/

Also Read:

Clock Verification for Mobile SoCs

CTO Interview: Dr. Zakir Hussain Syed of Infinisim

Clock Aging Issues at Sub-10nm Nodes


Fast Path to Baby Llama BringUp at the Edge

Fast Path to Baby Llama BringUp at the Edge
by Bernard Murphy on 09-26-2023 at 10:00 am

Baby Llama min

Tis the season for transformer-centric articles apparently – this is my third within a month. Clearly this is a domain with both great opportunities and challenges: extending large language model (LLM) potential to new edge products and revenue opportunities, with unbounded applications and volumes yet challenges in meeting performance, power, and cost goals. Which no doubt explains the explosion in solutions we are seeing. One dimension of differentiation in this race is in the underlying foundation model, especially GPT (OpenAI) versus Llama (Meta). This does not reduce to a simple “which is better?” choice it appears, rather opportunities to show strengths in different domains.

Llama versus other LLMs

GPT has enjoyed most of the press coverage so far but Llama is demonstrating it can do better in some areas. First a caveat – as in everything AI, the picture continues to change and fragment rapidly. GPT already comes in 3.5, 4, and 4.5 versions, Google has added Retro, LaMDA and PaLM2, Meta has multiple variants of Llama, etc, etc.

GPT openly aims to be king of the LLM hill both in capability and size, able from a simple prompt to return a complete essay, write software, or create images. Llama offers a more compact (and more accessible) model which should immediately attract edge developers, especially now that the Baby Llama proof of concept has been demonstrated.

GPT 4 is estimated to run to over a trillion parameters, GPT 3.5 around 150 billion, and Llama 2 has variants from 7 to 70 billion. Baby Llama is now available (as a prototype) in variants including 15 million, 42 million and 110 million parameters, a huge reduction making this direction potentially very interesting for edge devices. Notable here is that Baby Llama was developed by Andrej Karpathy of OpenAI (not Meta) as a weekend project to prove the network could be slimmed down to run on a single core laptop.

As a proof of concept, Baby Llama is yet to be independently characterized or benchmarked, however Karpathy has demonstrated ~100 tokens/second rates when running on an M1 MacBook Air. Tokens/second is a key metric for LLMs in measuring throughput in response to a prompt.

Quadric brings Baby Llama up on Chimera core in 6 weeks

Assuming that Baby Llama is a good proxy for an edge based LLM, Quadric made the following interesting points. First, they were able to port the 15 million parameter network to their Chimera core in just 6 weeks. Second, this port required no hardware changes, only some (ONNX) operation tweaking in C code to optimize for accuracy and performance. Third they were able to reach 225 tokens/second/watt, using a 4MB L2 memory, 16 GB/second DDR, a 5nm process and 1GHz clock. And fourth the whole process consumed 13 engineer weeks.

 

By way of comparison, they ran the identical model on an M1-based Pro laptop running the ONNX runtime with 48MB RAM (L2 + system cache) and 200 GB/sec DDR, with a 3.3 GHz clock. That delivered 11 tokens/second/watt. Quadric aims to extend their comparison to edge devices once they arrive.

Takeaways

There are obvious caveats. Baby Llama is a proof of concept with undefined use-rights as far as I know. I don’t know what (if anything) is compromised in reducing full Llama 2 to Baby Llama, though I’m guessing for the right edge applications this might not be an issue. Also performance numbers are simulation-based estimates, comparing with laptop performance rather than between implemented edge devices.

What you can do with a small LLM at the edge has already been demonstrated by recent Apple IoS/MacOS releases which now support word/phrase completion as you type. Unsurprising – next word/phrase prediction is what LLMs do. A detailed review from Jack Cook suggests their model might be a greatly reduced GPT 2 at about 34 million parameters. Unrelated recent work also suggests value for small LLMs in sensing (e.g. for predictive maintenance).

Quadric’s 6-week port with no need for hardware changes is a remarkable result, important as much in showing the ability of the Chimera core to adapt easily to new networks as in the performance claims for this specific example. Impressive! You can learn more about this demonstration HERE.

Also Read:

Vision Transformers Challenge Accelerator Architectures

An SDK for an Advanced AI Engine

Quadric’s Chimera GPNPU IP Blends NPU and DSP to Create a New Category of Hybrid SoC Processor


Optimizing Shift-Left Physical Verification Flows with Calibre

Optimizing Shift-Left Physical Verification Flows with Calibre
by Peter Bennet on 09-26-2023 at 6:00 am

Shift-left with Calibre

Advanced process nodes create challenges for EDA both in handling ever larger designs and increasing design process complexity.

Shift-left design methodologies for design cycle time compression are one response to this. And this has also forced some rethinking about how to build and optimize design tools and flows.

SemiWiki covered Calibre’s use of a shift-left strategy to target designer productivity a few months ago, focusing on the benefits this can deliver (the “what”). This time we’ll look closer at the “how” – specifically what Siemens call Calibre’s four pillars of optimization (these diagrams are from the Siemens EDA paper on this theme).

Optimizing Physical Verification (PV) means both delivering proven signoff capabilities in a focused and efficient way in the early design stages and extending the range of PV.

Efficient tool and flow Execution isn’t only about leading performance and memory usage. It’s also critical to reduce the time and effort to configure and optimize run configurations.

Debug in early stage verification is increasingly about being able to isolate which violations need fixing now and providing greater help to designers in quickly finding root causes.

Integrating Calibre Correction into the early stage PV flow can save design time and effort by avoiding potential differences between implementation and signoff tool checks.

Reading through the paper, I found it helpful here to think about the design process like this:

Current design

  • The portion of the design (block, functional unit, chip) we’re currently interested in
  • Has a design state, e.g. pre-implementation, early physical, near final, signoff

Design context

  • States of the other design parts around our current design

Verification intent

  • What we need to verify now for our current design
  • A function of current design state, context and current design objectives and priorities
  • Frequently a smaller subset of complete checks

We’ll often have a scenario like that below.

Sometimes we’ll want to suppress checks or filter out results from earlier stage blocks. Sometimes we might just want to check the top-level interfaces. Different teams may be running different checks on the same DB at the same time.

Verification configuration and analysis can have a high engineering cost. How to prevent this multiplying up over the wide set of scenarios to be covered as the design matures ? That’s the real challenge Calibre sets out to meet here by communicating a precise verification intent for each scenario, minimizing preparation, analysis, debug and correction time and effort.

Extending Physical Verification

Advanced node physical verification has driven some fundamental changes in both how checks are made and their increased scope and sophistication in the Calibre nmPlatform

Equation-based checks (eqDRC) that require complex mathematical equations using the SVRF (standard verification rule) format are one good example. And also one that emphasizes the importance of more programmable checks and fully integrating both checks and results annotation into the Calibre toolsuite and language infrastructure.

PERC (programmable electrical rule checking) is another expanding space in verification that spans traditional ESD and latch-up to newer checks like voltage dependent DRC.

Then there are thermal and stress analysis for individual chips and 3D stacked packages and emerging techniques like curvilinear layout checks for future support.

The paper provides a useful summary diagram (in far more detail than we can cover here).

 

Improving Execution Efficiency

EDA tool configuration is a mix of top-down (design constraints) and bottom-up (tool and implementation settings) – becoming increasingly bottom-up and complex as the flow progresses. But we don’t want all the full time-consuming PV config effort for the early design checks in a shift-left flow.

Calibre swaps out the traditional trial-and-error config search for a smarter, guided and AI-enabled one which understands the designer’s verification intent. Designers might provide details on the expected state (“cleanliness”) of the design and even relevant error types and critical parts of a design, creating targeted check sets that minimize run time.

Some techniques used by Calibre are captured below.

 

Accelerating Debug

Streamlining checks for the design context usefully raises the signal-to-noise ratio in verification reports. But there’s still work to do in isolating which violations need addressing now (for example, a designer may only need to verify block interfaces) and then finding their root causes.

Calibre puts accumulated experience and design awareness to work to extract valuable hints and clues to common root causes – Calibre’s debug signals. AI-empowered techniques aid designers in analyzing, partitioning, clustering and visualizing the reported errors.

Some of Calibre’s debug capabilities are shown below.

 

Streamlining Correction

If we’re running Calibre PV in earlier design stages, why not use Calibre’s proven correct-by-construction layout modifications and optimizations from its signoff toolkit for the fixes – eliminating risks from potential differences in implementation and signoff tool checks ? While Calibre’s primarily a verification tool, it’s always had some design fixing capabilities and is already tightly integrated with all leading layout flows.

But the critical reason is that layout tools aren’t always that good at some of the tasks they’ve traditionally been asked to do. Whether that’s slowness in the case of filler insertion or lack of precision in what they do – since they don’t have signoff quality rule-checking – meaning either later rework or increased design margining.

An earlier SemiWiki article specifically covered Calibre Design Enhancer’s capabilities for design correction.

The paper shows some examples of Calibre optimization.

 

Summary

A recent article about SoC design margins noted how they were originally applied independently at each major design stage. As diminishing returns from process shrinks exposed the costly over-design this allowed, this forced a change to a whole process approach to margining.

It feels like we’re at a similar point with the design flow tools. No longer sufficient to build flows “tools-up” and hope that produces good design flows, instead move to a more “flow-down” approach where we co-optimize EDA tools and design flows.

That’s certainly the direction Calibre’s shift-left strategy is following. building on these four pillars of optimization.

Find more details in the original Siemens EDA paper here:

The four foundational pillars of Calibre shift-left solutions for IC design & implementation flows.


Power Analysis from Software to Architecture to Signoff

Power Analysis from Software to Architecture to Signoff
by Daniel Payne on 09-25-2023 at 10:00 am

power analysis min

SoC designs use many levels of design abstraction during their journey from ideation to implementation, and now it’s possible to perform power analysis quite early in the design process. I had a call with William Ruby, Director of Porduct Marketing – Synopsys Low Power Solution to hear what they’ve engineered across multiple technologies.  Low-power IC designs that run on batteries need to meet battery life goals, and that is achieved through analyzing and minimizing power throughout the design lifecycle. High-performance IC designs also need to meet their power specifications, and lowering power during early analysis can also allow for increased clock rates which then boosts performance further. There are five EDA products from Synopsys that each provide power analysis and optimization capabilities to your engineering team from software to signoff.

Power-aware tools at Synopsys

The first EDA tool listed is Platform Architect, and that is used to explore architectures and even provide early power analysis, before any RTL is developed by using an architectural model that your team can run different use cases on. With the Platform Architect tool you can build a virtual platform for early software development, and to start verifying the hardware performance.

Once RTL has been developed, then an emulator like Synopsys ZeBu can be used to run actual software on the hardware representation. Following the emulation run, ZeBu Empower delivers power profiling of the entire SoC design so that you can know the sources of dynamic and leakage power quite early, before silicon implementation. These power profiles cover billions of cycles, and the critical regions are quickly identified as areas for improvements.

Zebu Empower flow

RTL Power Analysis

RTL power analysis is run with the PrimePower RTL tool using vectors from simulation and/or emulation, or even without vectors for what-if analysis. Designers can explore and get guidance on the effects of clock-gating, memory, data-path and glitch power. The power analysis done at this stage is physically-aware, and consistent with signoff power analysis results.

PrimePower – Three Stages

Gate-level Power Analysis

Logic synthesis converts RTL into a technology-specific gate-level netlist, ready for placement and routing during the implementation stage. The golden power signoff is done on the gate-level design using PrimePower. Gate-level power analysis provides you with average power, peak power, glitch power, clock network power, dynamic and leakage power, and even multi-voltage power. Input vectors can come from RTL simulation, emulation or vectorless. The RTL to GDSII flow is provided with the Fusion Compiler tool, where engineers optimize their Power, Performance and Area (PPA) goals.

Summary

Achieving energy efficiency from software to silicon is now a reality using the flow of tools and technologies provided by Synopsys. This approach takes the guesswork out of meeting your power goals prior to testing silicon, and has been proven by many design teams around the world. What a relief to actually know that your power specification has been met early in the design lifecycle.

Synopsys has a web page devoted to energy-efficient SoC designs, and there’s even a short overview video on low-power methodology. There’s also a White Paper, Achieving Consistent RTL Power Accuracy.

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WEBINAR: Why Rigorous Testing is So Important for PCI Express 6.0

WEBINAR: Why Rigorous Testing is So Important for PCI Express 6.0
by Daniel Nenni on 09-25-2023 at 8:00 am

PCIe IO bandwidth doubles every 3 years

In the age of rapid technological innovation, hyperscale datacenters are evolving at a breakneck pace. With the continued advancements in CPUs, GPUs, accelerators, and switches, faster data transfers are now paramount. At the forefront of this advancement is PCI Express (PCIe®), which has become the de-facto standard of interconnect for high-speed data transfers between processing and computing nodes.

Click here to register now!

Doubling Data Rates: The Trend Continues

The PCI-SIG® consortium, responsible for the PCIe interface, has a history of launching a new PCIe generation approximately every three years. This invariably has doubled the data rate over the past decade. PCI-SIG’s latest release, PCIe 6.0.1, ushers in multi-level Pulse Amplitude Modulation (PAM4) signaling, boasting a staggering transfer rate of 64 GT/s in one direction on a single lane. Notably, during the 2022 PCI-SIG DevCon, the announcement of PCIe 7.0 specification came, doubling the data rate to 128 GT/s, emphasizing both power efficiency and higher bandwidth.

Figure 1. PCI-SIG I/O Bandwidth doubles every 3 years. From PCI-SIG

 Stringent Testing for Compliance and Interoperability

It’s important to understand that beyond hyperscale data centers, the deployment of PCIe technology in fields like handheld devices, servers, automotive, industrial applications, and more demands high reliability and cost-effectiveness. This necessitates rigorous compliance testing for products to ensure they align with the PCIe 6.0.1 specification and can successfully interoperate with other PCIe devices.

Unveiling PAM4 Signaling and its Implications

The integration of PAM4 signaling in PCIe 6.0.1 is key. Unlike the Non-Return-to-Zero (NRZ) signaling, which used two distinct signal levels, PAM4 uses four, transmitting two bits of information within a single unit interval (UI). This modification introduces new challenges like cross-talk interferences, signal reflections, and power supply noise. The PCIe 6.0.1 specification has introduced the Signal-to-Noise Distortion Ratio (SNDR) to address these challenges, encapsulating both the traditional noise and non-compensable impairments within the electrical signal. Understanding of signal integrity issues in the high-speed communication channels due to cross-talk, reflection losses with frequency and time domain analysis  is the key. Channel measurement techniques and various signal enhancement techniques with PCIe 6.0 Transmitter and Receiver equalization are used to compensate for non-ideal channel characteristics.

Summary

The advancements in PCIe technology have paved the way for a new age of data transfer capabilities, with PCIe 6.0.1 and the forthcoming PCIe 7.0 setting new benchmarks. However, with greater capabilities come greater challenges, particularly in ensuring compliance and interoperability. Partnerships like Synopsys and Tektronix are leading the charge in addressing these challenges, ensuring that the technology not only meets but exceeds the demands of today’s digital age.

Join Our Webinar!

Want to delve deeper into PCIe simulations and electrical testing? Join our upcoming webinar on Tuesday October 10, from 9:00 am to 10:00 am PDT, where Synopsys and Tektronix industry experts will discuss the latest in PCIe technology and the significance of robust testing methodologies. Click here to register now!

Speakers:

David Bouse is a Principal Technology Leader at Tektronix and an active contributor to PCI-SIG with expertise in highspeed SERDES including transmitter and receiver test methodologies, DSP algorithms for NRZ/PAM4 signaling, clock characterization, and automation software architecture.

Madhumita Sanyal is a Sr. Staff Technical Manager for Synopsys high-speed SerDes portfolio. She has +17 years of experience in design and application of ASIC WLAN products, logic libraries, embedded memories, and mixed-signal IP.

About Synopsys

Synopsys, Inc. (Nasdaq: SNPS) is the Silicon to Software™ partner for innovative companies developing the electronic products and software applications we rely on every day. As an S&P 500 company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and offers the industry’s broadest portfolio of application security testing tools and services. Whether you’re a system-on-chip (SoC) designer creating advanced semiconductors, or a software developer writing more secure, high-quality code, Synopsys has the solutions needed to deliver innovative products. Learn more at www.synopsys.com.

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Next-Gen AI Engine for Intelligent Vision Applications

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TSMC’s First US Fab

TSMC’s First US Fab
by Daniel Nenni on 09-25-2023 at 6:00 am

WaferTech TSMC

TSMC originally brought the pure-play foundry business to the United States in 1996 through a joint venture with customers Altera, Analog Devices, ISSI, and private investors (no government money). Altera is now part of Intel but ADI is still a top TSMC customer and enthusiastic supporter. I have seen the ADI CEO Vincent Roche present at recent TSMC events and his TSMC partnership story is compelling. This joint venture was part of TSMC’s customer centric approach to business, responding directly to customer requests.

The WaferTech fab was established in Camas Washington (just North of the Oregon/Washington border) in 1996 with an investment of more than $1B which was a huge amount of money at the time. Production started two years later at .35 micron which was part of the Philips technology transfer that TSMC was founded upon. In 2000 TSMC bought out the partners and private investors, taking full control of the Washington fab. It is now called TSMC Fab 11 but clearly this fab was ahead of its time, absolutely.

From TSMC:

WaferTech focuses on Embedded Flash process technology while supporting a broad TSMC technology portfolio on line-widths ranging from 0.35-microns down to 0.16-microns. We specialize in helping companies deliver differentiated products and work with them on a number of customized and manufacturing “phase-in” projects. As a result, WaferTech delivers the latest generation semiconductors around the globe, supporting innovations in automotive, communications, computing, consumer, industrial, medical and military/aerospace applications.

To complement our world class process manufacturing services, WaferTech also provides test and analysis services at our Camas, Washington facility. Moreover, TSMC provides design, mask and a broad array of packaging and backend services at its other locations around the world. WaferTech also is a host for TSMC’s foundry-leading CyberShuttle™ prototyping services that help reduce overall design risks and production costs.

WaferTech, First U.S. Pure-play Foundry Ships Production Qualified Product ahead of Plan Issued by: Taiwan Semiconductor Manufacturing Company Ltd. Issued on: 1998/07/07

“With WaferTech on-line and shipping, TSMC customers gain another assured source for wafers produced to our standards of excellence,” said Ron Norris, president of TSMC, USA and a director of WaferTech. “Now TSMC is the only foundry in the world to transparently support customers from geographically dispersed sites.”

Ron Norris is another hire TSMC made with TI roots. Ron himself was a semiconductor legend. He started his career at TI and held executive level positions at Microchip in Arizona, Fairchild Semiconductor in Silicon Valley, and Data I/O Systems in Redmond WA, so he certainly knew the challenges of semiconductor manufacturing in the United States.

Historically, TSMC doesn’t just build fabs, TSMC builds communities. In fact, a TSMC fab itself is a community with everything you need to help maintain a work life balance. I have spent a lot of time in different fabs around the world but for the most part they were TSMC fabs in Taiwan. I still consider the Hsinchu Hotel Royal (walking distance from TSMC Fab 12A) as my second home. I remember flying in on my birthday one year and the staff had a mini birthday celebration when I arrived. Yes, they are that good, but I digress.

One thing you have to remember is that in Taiwan, working for TSMC brings status. You are a rockstar. Working for Samsung in South Korea has a similar aura. When TSMC breaks ground on a new fab location in Taiwan you can expect a whole support ecosystem to develop around it with everything a TSMC fab needs to be successful including housing and university level education for recruiting and employee growth.

Bottom line: Working for TSMC in Taiwan is like joining a very large and very successful family business.

Unfortunately, in Camas Washington, that was not the case. The WaferTech campus is a 23 acre complex housed on 260 acres. The main fabrication facility consists of a 130,000 square foot 200mm wafer fabrication plant.  Additional fabs were planned but never built, a support ecosystem never formed, thus the TSMC Taiwan fab recipe was called out as a failure in the US.

Many reasons have been sited for this “failure” including high costs, problems attracting local talent, and timing (soft economy), but in my opinion it also had a lot to do with the rockstar factor. In the US we had forgotten or did not know yet how important semiconductors were to modern life and TSMC was not a big name in the US like it is today.

Now that TSMC is building fabs in Arizona, Kumamoto Japan, and Dresden Germany it will be interesting to see how different the TSMC experience is in these world wide locations.

Also Read:

How Taiwan Saved the Semiconductor Industry

Morris Chang’s Journey to Taiwan and TSMC

How Philips Saved TSMC

The First TSMC CEO James E. Dykes

Former TSMC President Don Brooks

The TSMC Pivot that Changed the Semiconductor Industry!

The TSMC OIP Backstory


Podcast EP183: The Science and Process of Semiconductor Innovation with Milind Weling

Podcast EP183: The Science and Process of Semiconductor Innovation with Milind Weling
by Daniel Nenni on 09-22-2023 at 10:00 am

Dan is joined by Milind Weling, the Head of Device and Lab to Fab Realization and co-founder of the neuro-inspired Computing Incubator of EMD Electronics. Previously he was senior vice president for Intermolecular. He led customer programs and operations where he drove the discovery and optimization of new materials, integrated module solutions and leading-edge devices. Milind is a senior engineering and management professional with extensive experience in advanced memory and logic technology development, DFM and design-process interactions, new product introduction, and foundry management. He holds 50+ patents and has co-authored over 70 technical papers, primarily focused on semiconductor process technology, device reliability and integration.

Dan explores the approaches used to achieve semiconductor innovation with Milind. The methods and processes applied to advance the state-of-the-art are discussed in detail, across several application areas. It turns out innovation is not driven by “eureka” moments of invention, but rather by focused and sustained work to find the best path forward.

Semiconductor Devices: 3 Tricks to Device Innovation by Milind Welling

The views, thoughts, and opinions expressed in these podcasts belong solely to the speaker, and not to the speaker’s employer, organization, committee or any other group or individual.