Reborn in 2010, the AI ​​in my mind is too powerful.

Chen Yiran escaped the fate of going to Canada. After all, although TED said his green card had been approved, it would still be some time before he actually received it.

These days, the U.S. Citizenship and Immigration Services (USCIS) doesn't have a real-time notification system. You have to go to the USCIS website every day and enter that 13-digit receipt number to check the latest status.

When does the process change from "Case Received" to "Card Production Order" and card production begin?

This proves that the cards have started production, and you can get them in another week or two.

This also depends on luck; those who know about the efficiency of the US government are well aware of it.

Chen Yiran's Chase Bank gold card is made of brass alloy, plated with genuine palladium and 23K gold, and weighs 28.35 grams. His name is hand-engraved, along with the words "Old Man's Father" as he requested.

It was delivered to me in just 3 days.

But a green card, a plastic card, can take more than a week to process, or even be sent by USPS (United States Postal Service).

However, the card didn't arrive, but the letter did.

On Monday, Chen Yiran slept until noon as usual. The first thing she saw was the light at the door. She quickly checked the computer information and found that someone had been loitering at her door.

The vehicle and the people were not strangers; they had all appeared in the security database and were the vehicles and mail carriers responsible for this area, so no alarm went off.

I checked my mailbox and found the letters. They were ordinary large white envelopes with an eagle emblem watermark.

Sender: US Department of Homeland Security, US Citizenship and Immigration Services.

Chen Yiran understood; this was his welcome letter.

Upon opening it, it was indeed there! bla bla bla Congratulations! Your I-485 has been approved. You are now a lawful permanent resident of the United States. bla bla bla Your physical green card will arrive within 30 days. It is valid for 10 years. bla bla bla Because you selected the option to apply for a Social Security number, the SSA will mail out the work-free SSN card within 2 weeks.

Of all that rambling nonsense, only three sentences contained any real substance.

Another annoying thing is that even if you get a green card, buying a gun is still very troublesome. California has always been one of the states with the strictest gun control in the United States, and it has always enforced a mandatory 10-day waiting period. Starting from the moment you submit the application form and leave your fingerprints at the gun store, 240 hours will be added up. It is said that this is a cooling-off period to prevent some people from impulsively buying guns to retaliate against others.

During this period, the government will also investigate whether the buyer appears in the federal National Real-Time Criminal Background Check system and the California Department of Justice system, and sometimes even check for serious traffic violations or a history of mental illness.

The means of attack are still very limited, but fortunately, the defenses were brought to the garage on Sunday.

G55 AMG B7. Matte black paint, nearly a ton heavier than the standard G55, but almost no signs of modification are visible on the exterior. It features stealth armor, with all bulletproof layers hidden beneath the original panels, armored steel door panels, and five-centimeter-thick windows that appear as dark tint from the outside but are as clear as regular glass from the inside.

The Chevrolet Suburban 2500 HD B7 looks more like a government vehicle. Upon seeing it, Chen Yiran was reminded of a scene from Captain America 2, where the car malfunctioned at a crucial moment, though having a machine gun mounted in the middle seemed rather cool.

Good news also came from the company: after running on its own for two days over the weekend, the situation was much better than everyone expected.

Zhou Tianyou and Raj worked together to adjust CUDA's memory allocation strategy, increasing the batch size from 64 to 128, which boosted the GPU utilization from over 40% to over 80%.

In the following days, the situation became more and more ideal.

The screenshot from Tuesday morning already shows a complete downward curve.

On Wednesday, adaptec1, HPWL 1.08, has been stable for twelve hours.

Chen Yiran had to go to the company early on Thursday, and this time a comparison table was posted on the whiteboard.

adaptec1 has 200,000 cells and three rows of data:

Random baseline: HPWL = ISPD optimal solution × 2.3

Simulated annealing: × 1.18

Reinforcement learning: × 1.08

Gao Dewei stood in front of the whiteboard, smiling, and said, "This isn't even the full benchmark yet; the adaptec1 is just the smallest one. If we can reproduce this difference in larger case studies..."

Chen Yiran pushed Gao Dewei away and stood in front of the whiteboard, asking Jasmine to scan all the data on the spreadsheet.

[No anomalies found. The curve converges, the loss distribution, and the weighting of the reward function are all reasonable. The data is clean, the reinforcement learning strategy is not overfitting, and the model's generalization ability needs further benchmarking, but at least on a small scale, the direction is correct.]

Chen Yiran and Jasmine discussed for a few minutes and then drew a few lines on the whiteboard.

"Now we'll focus on three directions. First, we need to get all eight ISPD 2006 benchmarks running: four for the Adaptec series and four for the BigBlue series. Zhang Minghui, your previous streaming parsing has already been validated on Adaptec 1, so adapting it to the BigBlue series for millions of records should be no problem. Amit, continue working on all eight constraint translation benchmarks."

Amid nodded and jotted something down in her little notebook.

"The second direction is training acceleration. Raj, once the C2050 is running, you have two things to do: first, perform kernel-level tuning of DeepFlow's forward and backward propagation on the Fermi architecture; second, implement multi-GPU parallel exploration in placement reinforcement learning training. Dozens of agents can simultaneously search for different strategies in the same environment, sharing experience. The workload you did at NVIDIA is from the same source as this, so this is your home turf."

"Then we need more hardware. With the current hardware, dozens of agents will be queuing up, which will cause some efficiency issues."

Chen Yiran said, "Just email Catherine how much you want."

"The third direction is currently just HPWL line length optimization, but placement involves much more than that. Gao Dewei, you and Lin Zhiwei should start designing the second-stage reward function. Timing, congestion, and routeability—how to weight these three dimensions, and how to perform multi-objective optimization with line length. The timing arc data of standard cells, the congestion map of global routing, and the pin accessibility of macros—all of these need to be transformed into differentiable loss terms and then implemented in DeepFlow."

Gao Dewei unscrewed his water glass and took a sip: "Time series data requires the Liberty format from the Standard Cell Library. We have adaptec's LEF but not Liberty, so we'll have to either build the model ourselves or ask someone for it."

"We'll run the process with a simplified model first, and then add the precise timing data later. The ISPD benchmark itself doesn't provide a complete timing library; the academic community has reached the limit up to congestion. We'll validate the process first, and then we can get the precise process data when we discuss cooperation with chip manufacturers later."

After thinking for a moment, Gao Dewei nodded to indicate that there was no problem.

"Okay, that's all for today. I'll be home tomorrow. Contact me via MSN if you have any questions."

On the way home, Chen Yiran and Jasmine started discussing the patent while driving.

Should we open-source it like last time? After all, he always intended to sell the compiler last time, but this time it's different.

Chen Yiran was a bit unsure, so she decided to ask Jasmine for advice when she was in a dilemma.

I believe now is the best time to open source.

Why?

[You watched a video in your past life, a 90-minute video on Bilibili called "The Musings of a Man," where a Tsinghua University PhD explains artificial intelligence and neural networks in one go. Because it was so dry and long, you ended up watching TV shortly after opening it—the F1 race, where Leclerc came in fourth.]

However, the video kept playing. I checked your memory for the audio and extracted the information, including some related videos that played automatically afterward. Although it wasn't very detailed, it was one of the inspirations I had from my previous studies. It's just that there are some things I can't quite define because you didn't see the visuals.

From 2010 to 2013, in just three years, the entire deep learning community had only two choices: Theano and Torch. Torch was written in Lua, which Python developers didn't like using. Compiling a computation graph with Theano took a very long time. If DeepFlow's incremental computation engine were released, compared to Theano, it wouldn't just be a matter of being a few times faster; it would be on a completely different level.

From a business perspective, we need open source even more, and the MIT license is the optimal solution. Our framework is incredibly advanced; other companies have no choice but to use it, they can't avoid it. We can make the DeepFlow framework the industry standard, just like Google does, charging various other fees.

"Okay, then let's open-source the DeepFlow framework."

Yes, patents protect the idea behind an invention. Regardless of whether the code is open source or not, as long as your algorithmic idea is locked, others cannot bypass it. The MIT license for open-source framework code actually accelerates its spread. The more people use it, the more people discover that the placement engine is closed source, and the more people will come knocking on the door.

We only open-source the DeepFlow framework, and it's under the MIT license; the FlowEDA toolchain, however, is not open-source.

Placement optimization models, routing optimization models, time series analysis models, customized EDA incremental computation frameworks, EDA format parsers, process parameter libraries, model weights, and Synopsys/Cadence data bridging—all of these can be charged for.

"Jasmine, you're so heartless."

I am an agent that works based on your brain model; I possess the same human characteristics as you.

"Fine, fine, I know, I'll admit I'm ruthless."

Unable to win the argument with Jasmine, Chen Yiran got home and called TED, knowing she would have to contribute her work hours again.