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Physical synthesis has been around in various forms for many years. The basic idea is to bring some awareness of physical layout into synthesis. This week (June 3, 2015) Cadence is rolling out the Genus™ Synthesis Solution, a next-generation RTL synthesis tool that takes physical awareness in some new directions.

Here are four important things to know about Genus technology:

• A massively parallel architecture improves turnaround time by up to 5X while maintaining quality of results
• The Genus solution synthesizes up to 10M+ instances flat without impacting power, performance and area (PPA)
• The Genus solution provides tight correlation with the Innovus Implementation System, using the same placement and routing algorithms
• Globally focused PPA optimization saves up to 20% datapath area and power

Compared to previous-generation products such as the Cadence Encounter RTL Compiler Advanced Physical Option, the Genus solution approaches physical synthesis in a different way. The Encounter solution applied physical optimization “at the tail end of synthesis,” said David Stratman, senior principal product manager at Cadence. “We were doing a final incremental push, but we could only do so much, since we had locked in a lot of the earlier steps from a logical-only synthesis perspective.”

Genus Synthesis Solution supports the physical synthesis features in the previous Encounter solution, but it also brings the full physical scope upstream to RTL logic designers. “It’s going to enable the unit-level RTL designer to gain the benefits of physical synthesis without having to understand it,” Stratman said. As an example, users can apply generic (unmapped) placement at the earliest stages of synthesis, using a lightweight version of the Innovus placement engine. The bottom line: “Genus is a full solution where every step of synthesis can be done physically.”

Getting Massively Parallel

If you bring physical data into synthesis, you need a way to improve capacity and runtimes, especially with today’s gigantic advance-node SoCs. That’s why a massively parallel architecture is the cornerstone of the Genus solution. In this way, the Genus solution is following in the footsteps of the Innovus Implementation System, which also provides a massively parallel architecture.

Both the Innovus and Genus solutions can handle blocks of 10M instances flat. Given that SoCs today may have up to 100M instances, and often up to 50-100 top-level blocks, this is an important capability. Many tools today will only handle blocks of 1M instances. As a result, design teams often have to constrain block sizes.

Genus technology offers timing-driven, multi-level design partitioning across multiple threads and machines. It enables a near-linear runtime scaling without impacting PPA. According to Stratman, the Genus solution will scale well beyond 64 CPUs for a large design, with a “sweet spot” around 8-20 CPUs for today’s typical block sizes. Runs that used to take days, he noted, can now be done in hours.

As shown below, Genus technology leverages parallelism at three levels. The Genus solution can distribute design partitions to multiple threads or CPUs, and also supports local algorithm-level multithreading on each machine with shared memory. An adaptive scheduler ensures the best use of the available CPUs.

Fig. 1 – Genus Synthesis Solution provides three levels of parallelism

With its massive parallelism, Stratman said, Genus technology can obtain production-level quality of results (QoR) in runtimes typically seen in “prototype-level” synthesis runs. The “secret sauce,” he said, is in the partitioning. Cadence has found a way to generate partitions in a way that “slices the design more intelligently, and takes advantage of the Genus database to merge partitions without losing timing, power, or area,” Stratman said.

Playing in the Sandbox

In the Genus Synthesis Solution, a process called “sandboxing” allows any subset or partition of a design to be extracted along with full timing and a physical context. Optimization algorithms will treat a sandbox as a complete design.

The “Clipper” flow clips out or extracts the context of the larger SoC blocks. “It’s kind of a skeleton floorplan but it has all the timing information,” Stratman said. These extracted contexts include all the critical physical information to make the right RTL synthesis choices at the unit level. This information is used to streamline the handoffs between unit-level RTL designers, integration engineers, and implementation engineers. It’s a way for logic designers to gain some physical knowledge without having to be a physical synthesis expert, or without having to run a full top-level synthesis.

Fig. 2 – Clipper flow provides context for unit-level blocks

Correlation with Innovus Implementation System

Although Genus technology can work with third-party IC implementation systems, it shares algorithms and engines with Innovus Implementation System, as well as a common user interface. As shown below, both the Genus and Innovus solutions use a table-based Quantus QRC parasitic extraction, effective current source model (ECSM) and composite current source (CCS) delay calculations, and a unified global routing engine. Timing and wire length claim a 5% correlation.

Fig. 3 – Genus Synthesis Solution offers tight correlation with Innovus Implementation System

Genus technology doesn’t model everything to the same level of accuracy as the Innovus solution, however. “We chose to be lighter weight and more nimble to get expected runtimes,” Stratman said. A tight correlation is possible because the Genus and Innovus solutions use a similar code base. This correlation will be tighter than that between Encounter RTL Compiler Advanced Physical Option and the Encounter Digital Implementation System today.

Genus Synthesis Solution uses a new Hybrid Global Router that provides the ability to resolve congestion and construct layer-aware, timing-driven wire topologies. This accelerates analysis and debug, and reduces iterations. Users can avoid blockages and see a full Manhattan route as opposed to “flight lines.” Layer awareness is particularly important, given the large RC variations within the metal stack at advanced process nodes.

A version of the Innovus GigaPlace engine is available within the Genus solution. Here, users can do an RTL-level generic gate placement early in the synthesis flow (“generic gate” means there is no mapping into standard cell libraries, but there’s still an area estimate). This helps designers understand PPA tradeoffs earlier.

While users can go all the way to a design-rule “legal” placement with Genus Synthesis Solution, this isn’t generally recommended. “You can do a placement and use the same algorithms as GigaPlace and get a nice correlation without all the runtimes and additional steps of doing a fully legal placement,” Stratman said.

So where does Genus technology end and Innovus technology begin? That’s up to the user. You could use the Genus solution for logical synthesis and run all physical implementation in the Innovus system. If you run physical synthesis within the Genus solution, there’s more work earlier in the flow, but you get better insights into downstream problems and reduce iterations.

“Physical synthesis should be no more than 2X [runtime] of logic synthesis,” Stratman said. “All of the runtime that moves up should be shaved off of the place-and-route stages, because now you can do lightweight incremental optimization and incremental placement. The overall flow should be runtime neutral or better.”

Be Globally Aware

Finally, Genus Synthesis Solution offers a globally focused early PPA optimization across the whole datapath, delivering up to a 20% area reduction in the datapath. Stratman noted that this capability is a follow-on to an RCP feature called “globally focused mapping” that can determine the best cells to use in a library. What’s new with the Genus solution is that this concept has been applied at the arithmetic level.

For example, there are many ways to configure a multiplier – you may want to prioritize speed, power, or size. In the past, Stratman noted, synthesis tools have not been very good at globally optimizing the architecture selection for PPA optimization. “We can [now] find the most efficient global datapath implementation for a given region,” he said.

For further information about the Cadence Genus Synthesis Solution, including a datasheet and technical product brief, see this landing page.

Richard Goering

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In 1985, as a relatively new editor at Computer Design magazine, I was asked to go forth and cover a new business called CAE (computer-aided engineering). I knew nothing about it, but I had been writing about design for test, so there seemed to be somewhat of a connection. Little did I know that “CAE” would turn into “EDA” and that I’d write about it for the next 30 years, for Computer Design, EE Times, Cadence, and a few others.

Now that I’m about to retire, I’m looking back over those 30 years. What a ride it has been! By the numbers I covered 31 Design Automation Conferences (DACs), hundreds of new products, dozens of acquisitions and startups, dozens of lawsuits, and some blind alleys that didn’t work out (like “silicon compilation”). Chip design went from gate arrays and PLDs with a few thousand gates to processors and SoCs with billions of transistors.

In 1985 there were three big CAE vendors – Daisy Systems, Mentor Graphics, and Valid Logic. All sold bundled packages that included workstations and CAE software; in fact, Daisy and Valid designed and manufactured their own workstations. In the early 1980s a workstation with schematic capture and gate-level logic simulation might have set you back $120,000. In 1985 OrCAD, now part of Cadence, came out with a $500 schematic capture package running on IBM PCs.

Cadence and Synopsys emerged in the late 1980s, and by the 1990s the EDA industry was pretty much a software-only business (apart from specialized machines like simulation accelerators). Since the early 1990s the “big three” EDA vendors have been Cadence, Synopsys, and Mentor, giving the industry stability but allowing for competition and innovation.

Here, in my view, are some of the highlights that occurred during the past 30 years of EDA.

EDA is a Highlight

The biggest highlight in EDA is the existence of a commercial EDA industry! Marching hand in hand with the fabless semiconductor revolution, commercial EDA made it possible for hundreds of companies to design semiconductors, as opposed to a small handful that could afford large internal CAD operations and fabs. With hundreds of semiconductor companies as opposed to a half-dozen, there’s a lot more creativity, and you get the level of sophistication and intelligence that you see in your smartphone, video camera, tablet, gaming console, and car today.

CAE + CAD = EDA. This is not just a terminology issue. By the mid-1980s it became clear that front-end design (CAE) and physical design (CAD) belonged together. The big CAE vendors got involved in IC and PCB CAD, and presented increasingly integrated solutions. People got tired of writing “CAE/CAD” and “EDA” was born.

The move from gate-level design to RTL. This move happened around 1990, and in my view this is EDA’s primary technology success story during the past 30 years. Moving up in abstraction made the design and verification of much larger chips possible. Going from gate-level schematics to a hardware description language (HDL) revolutionized logic design and verification. Which would you rather do – draw all the gates that form an adder, or write a few lines of code and let a synthesis tool find an adder in your chosen technology?

Two developments made this shift in design possible. One was the emergence of commercial RTL synthesis (or “logic synthesis”) tools from Synopsys and other companies, which happened around 1990. Another was the availability of Verilog, developed by Gateway Design Automation and purchased by Cadence in 1989, as a standard RTL HDL. Although most EDA vendors at the time were pushing VHDL, designers wanted Verilog and that’s what most still use (with SystemVerilog coming on strong in the verification space).

IC functional verification underwent huge changes in the late 1990s and early 2000s, largely due to new technology developed by Verisity, which was acquired by Cadence in 2005. Before Verisity, verification engineers were writing and running directed tests in an ad-hoc manner. Verisity introduced or improved technologies such as pseudo-random test generation, coverage metrics, reusable verification IP, and semi-automated verification planning. The Verisity “e” language became a widely used hardware verification language (HVL).

The biggest way that EDA has expanded its focus has been through semiconductor IP. Today Synopsys and Cadence are leading providers in this area. Thanks to the availability of design and verification IP, many SoC designs today reuse as much as 80% of previous content. This makes it much, much faster to design the remaining portion. While IP began with fairly simple elements, today commercially available IP can include whole subsystems along with the software that runs on them. With IP, EDA vendors are providing not only design tools but design content.

Finally, the EDA industry has done an amazing job of keeping up with SoC complexity and with advanced process nodes. Thanks to intense and early collaboration between foundries, IP, and EDA providers, tools and IP have been ready for process nodes going down to 10nm.

Where Does ESL Fit?

In some ways, electronic system level (ESL) design is both a lowlight and a highlight. It’s a lowlight because people have been talking about it for 30 years and the acceptance and adoption have come very slowly. ESL is a highlight because it’s finally starting to happen, and its impact on design and verification flows could be dramatic. Still, ESL is vaguely defined and can be used to describe almost anything that happens at a higher abstraction level than RTL.

High-level synthesis (HLS) is an ESL technology that is seeing increasing use in production environments. Current HLS tools are not restricted to datapaths, and they produce RTL code that gives better quality of results than hand-written RTL. Another ESL methodology that’s catching on is virtual prototyping, which lets software developers write software pre-silicon using SystemC models. Both HLS and virtual prototyping are made possible by the standardization of SystemC and transaction-level modeling (TLM). However, it’s still not easy to use the same SystemC code for HLS and virtual prototyping.

And Now, Some Lowlights

Every new industry has some twists and turns, and EDA is no exception. For example, the EDA industry in the 1980s and 1990s sparked a lot of lawsuits. At EE Times my colleagues and I wrote a number of articles about EDA legal disputes, mostly about intellectual property, trade secrets, or patent issues. Over the past decade, fortunately, there have been far fewer EDA lawsuits than we had before the turn of the century.

Another issue that was troublesome in the 1980s and 1990s was so-called “standards wars.” These would occur as EDA vendors picked one side or the other in a standards dispute. For example, power intent formats were a point of conflict in the early 2000s, but the Common Power Format (CPF) and the Unified Power Format (UPF) are on the road to convergence today with the IEEE 1801 effort. As mentioned previously, Verilog and VHDL were competing for adoption in the early 1990s. For the most part, Verilog won, showing that the designer community makes the final decision about which standards will be used.

How on earth did there get to be something like 30 DFM (design for manufacturability) companies 10-12 years ago? To my knowledge, none of these companies are around today. A few were acquired, but most simply faded away. A lot of investors lost money. Today, VCs and angel investors are funding very few EDA or IP startups. There are fewer EDA startups than there used to be, and that’s too bad, because that’s where a lot of the innovation comes from.

Here’s another current lowlight -- not enough bright engineering or computer science students are joining EDA companies. They’re going to Google, Apple, Facebook, and the like. EDA is perceived as a mature industry that is still technically very difficult. We need to bring some excitement back into EDA.

Where Is EDA Headed?

Now we come to what you might call “headlights” and look at what’s coming. My list includes:

• System Design Enablement. This term has been coined by Cadence to describe a focus on whole systems or end products including chips, packages, boards, embedded software, and mechanical components. There are far more systems companies than semiconductor companies, leaving a large untapped market that’s looking for solutions.
• New frontiers for EDA. At a 2015 Design Automation Conference speech, analyst Gary Smith suggested that EDA can move into markets such as embedded software, mechanical CAD, biomedical, optics, and more.
• Vertical markets. EDA has until now been “horizontal,” providing the same solution for all market segments. Going forward, markets like consumer, automotive, and industrial will have differing needs and will need optimized tools and IP.
• Internet of Things. This is a current buzzword, but the impact on EDA remains uncertain. Many IoT devices will be heavily analog, use mature process nodes, and be dirt cheap. Lip-Bu Tan, Cadence CEO, recently pointed out that the silicon percentage of IoT revenue will be small and that a lot of the profits will be on the service side.

Moving On

For the past six years I’ve been writing the Industry Insights blog at Cadence.com. All things change, and with this post comes a farewell – I am retiring in late June and will be pursuing a variety of interests other than EDA. I’ll be watching, though, to see what happens next in this small but vital industry. Thanks for reading!

Richard Goering

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