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# Lessons from David Patterson
- URL: https://www.antoinebuteau.com/lessons-from-david-patterson/
- Published: 2026-06-26T02:53:22.000Z
- Updated: 2026-07-18T21:49:07.000Z
- Description: David Patterson co-invented RISC architecture, later helping develop RAID storage, the open-source RISC-V instruction set, and Google’s Tensor Processing Unit. His career offers a framework for hardware engineering, academic research, and strategic choices across technical work.
- Author: Antoine Buteau
- Tags: Profile, AI & Machine Learning Profiles

![Visual summary of operating lessons from David Patterson.](https://www.antoinebuteau.com/content/images/2026/06/lessons-from-david-patterson-profile-infographic.webp)

## Lessons from David Patterson

David Patterson co-invented the RISC architecture, which permanently changed how microprocessors are built. He later helped develop RAID storage, the open-source RISC-V instruction set, and Google's Tensor Processing Unit. This collection organizes his advice on hardware engineering, academic research, and career strategy.

### Part 1: Academic Research & Mentorship

1. **On Initiative:** "Show initiative, for fortune favors the bold. Don't wait for professors to tell you what to do; if we were good managers, we probably wouldn't be faculty." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
2. **On Responsibility:** "Professors offer opportunities, but it is what the student does with those opportunities that makes or breaks their career." — [*Source: \[Advice to Graduate Students*](https://www.berkeley.edu/?ref=antoinebuteau.com)*\]*
3. **On Reverse Mentorship:** "Students should teach their professors about what they are working on, including what they have learned outside of the classroom." — [*Source: \[Penn State Research Notes*](https://www.psu.edu/?ref=antoinebuteau.com)*\]*
4. **On Early Involvement:** "Get involved in a research project as an undergraduate student. A classic thing to do is do well in a class and talk to your professor afterwards about whether there are things that you can be involved in." — [*Source: \[Medium Reflections on Academia*](https://medium.com/?ref=antoinebuteau.com)*\]*
5. **On Selecting Problems:** "Avoid choosing issues that are too narrow or lack real-world impact; pick something where the solution actually changes behavior." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
6. **On Ignoring Constraints:** "Academic research should intentionally ignore the legacy constraints that product companies are forced to maintain, in order to find the actual optimum." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
7. **On Building Teams:** "The best academic research comes from small, highly motivated teams of graduate students trying to prove the entire industry wrong." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
8. **On Grades vs. Research:** "Focusing strictly on a 4.0 GPA at the expense of early research involvement is a mistake if your goal is to be a creator of new knowledge." — [*Source: \[Wisconsin CS Seminar*](https://www.wisc.edu/?ref=antoinebuteau.com)*\]*
9. **On the Role of Universities:** "The university is the ideal place to build prototypes that fail, because the only consequence of failure is a learning experience." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*

### Part 2: Hardware Design Philosophy

1. **On Simplicity:** "Simplicity favors regularity. Coming up with simple, elegant solutions is often harder than building complexity." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
2. **On the RISC Premise:** "Processor complexity was wasting transistor budgets; the best way to improve performance was to strip designs down to their bare bones." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
3. **On Counter-Intuitive Design:** "The prevailing wisdom in the 1970s was that the best way to exploit semiconductor technology was to increase complexity. We took the counter-intuitive opposite approach." — [*Source: \[Berkeley News*](https://news.berkeley.edu/?ref=antoinebuteau.com)*\]*
4. **On Instruction Sets:** "An architecture is an interface between the hardware and the software. Making it smaller meant the hardware could be much faster." — [*Source: TEDxNiendorf 2024*](https://www.youtube.com/watch?v=CfKogTlit58&ref=antoinebuteau.com)
5. **On the Arm Architecture:** "The 'R' in ARM stands for RISC. They shipped 10 billion ARM processors last year, more than one for every person on the planet." — [*Source: \[Berkeley Engineering Profiles*](https://engineering.berkeley.edu/?ref=antoinebuteau.com)*\]*
6. **On Compilers over Hardware:** "Move the burden of managing execution from silicon to the compiler. Software is easier to change than hardware." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
7. **On Measuring Performance:** "Performance is determined by execution time, not just clock rate or instruction count in isolation." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
8. **On Common Cases:** "Make the common case fast. This is the most important and pervasive principle of computer design." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
9. **On Good Design:** "Good design demands good compromises, often finding the balance between instruction count and clock cycle time." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
10. **On Contrarian Approaches:** "RISC was a contrarian approach. We were a university group proving that the largest industry players were building chips the wrong way." — [*Source: \[mvdirona.com Technical Blog*](https://mvdirona.com/?ref=antoinebuteau.com)*\]*

### Part 3: The Semiconductor Industry & Moore's Law

1. **On Moore's Law:** "Moore's Law is over. It was a great 50-year run, but we are now in the era where transistor density no longer doubles every 18 months." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
2. **On Dennard Scaling:** "When Dennard scaling ended, we could no longer count on transistors getting more power-efficient as they got smaller, changing the entire thermal budget of chips." — [*Source: \[Turing Award Lecture*](https://amturing.acm.org/?ref=antoinebuteau.com)*\]*
3. **On the Golden Age:** "The end of Moore's Law is not the end of progress; it is a new Golden Age for computer architecture." — [*Source: \[Turing Award Lecture*](https://amturing.acm.org/?ref=antoinebuteau.com)*\]*
4. **On Silicon Economics:** "The cost of a chip is proportional to the fourth power of its area. Small, simple designs have massive economic advantages." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
5. **On Industry Stagnation:** "Without the free performance lunch of Moore's Law, hardware designers actually have to innovate again instead of just waiting for the next fab node." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
6. **On Legacy Architectures:** "Companies become trapped by their own success, forced to maintain decades of backward compatibility that drags down the efficiency of modern silicon." — [*Source: \[Software Engineering Daily*](https://softwareengineeringdaily.com/?ref=antoinebuteau.com)*\]*
7. **On Fabrication Costs:** "As the cost of cutting-edge fabs reaches tens of billions of dollars, only a few companies can afford to manufacture them, concentrating the industry." — [*Source: TEDxNiendorf 2024*](https://www.youtube.com/watch?v=CfKogTlit58&ref=antoinebuteau.com)
8. **On Transistor Budgets:** "When we started, we had a budget of thousands of transistors. Today we have billions. The challenge changed from fitting everything in, to deciding what to do with the excess." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
9. **On Amdahl's Law:** "Amdahl's Law strictly limits the speedup you can get from parallelizing a program if even a small fraction of the code remains sequential." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*

### Part 4: Building Systems

1. **On RAID:** "We realized that linking together a redundant array of inexpensive disks could outperform a single massive, expensive mainframe drive." — [*Source: \[Berkeley Research History*](https://www.berkeley.edu/?ref=antoinebuteau.com)*\]*
2. **On Reliability:** "The goal of RAID wasn't just to be cheaper; it was to use probability to make a system out of unreliable parts more reliable than a single expensive part." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
3. **On Network of Workstations (NOW):** "Why buy a supercomputer when you can connect hundreds of desktop workstations over a fast local network to achieve the same floating-point operations?" — [*Source: \[Berkeley Engineering Profiles*](https://engineering.berkeley.edu/?ref=antoinebuteau.com)*\]*
4. **On Fault Tolerance:** "In large systems, failure is not an anomaly; it is a statistical certainty. Software must be designed to expect and tolerate component failures." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
5. **On Bottlenecks:** "A system is only as fast as its slowest component. Improving CPU speed without improving memory and disk access just creates a different bottleneck." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*
6. **On Commodity Hardware:** "The PC revolution proved that commodity hardware scales faster than custom enterprise hardware. NOW and RAID just applied commodity economics to the datacenter." — [*Source: \[Software Engineering Daily*](https://softwareengineeringdaily.com/?ref=antoinebuteau.com)*\]*
7. **On the Cloud:** "The Network of Workstations project was essentially a precursor to modern cloud computing— treating a massive cluster of generic machines as a single resource." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
8. **On Tape Backup:** "RAID didn't eliminate the need for backups, it just eliminated the downtime from single-drive failures. You still need off-site backups." — [*Source: \[Berkeley Research History*](https://www.berkeley.edu/?ref=antoinebuteau.com)*\]*
9. **On System Abstractions:** "A successful system hides the complexity of its underlying components from the end user without sacrificing performance." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*

### Part 5: Artificial Intelligence & Domain-Specific Architectures

1. **On Domain-Specific Architectures (DSAs):** "As general-purpose processors hit performance walls, we have to build domain-specific architectures tailored to particular problems like machine learning." — [*Source: \[Turing Award Lecture*](https://amturing.acm.org/?ref=antoinebuteau.com)*\]*
2. **On the Google TPU:** "The Tensor Processing Unit was designed because we realized running neural networks on general-purpose CPUs at Google's scale would require doubling the size of our datacenters." — [*Source: Google I/O 2025*](https://www.youtube.com/watch?v=IzALjgpLGa4&ref=antoinebuteau.com)
3. **On Matrix Multiplication:** "Deep learning fundamentally reduces to massive matrix multiplications. If you build hardware optimized exclusively for that, you get exponential efficiency gains." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
4. **On Hardware/Software Co-design:** "The TPU succeeded because we co-designed the silicon directly with the TensorFlow software stack, rather than developing them in silos." — [*Source: \[Software Engineering Daily*](https://softwareengineeringdaily.com/?ref=antoinebuteau.com)*\]*
5. **On AI's Carbon Footprint:** "Training massive AI models consumes vast energy. We must aggressively optimize hardware and datacenters to mitigate the carbon footprint of machine learning." — [*Source: Google I/O 2025*](https://www.youtube.com/watch?v=IzALjgpLGa4&ref=antoinebuteau.com)
6. **On Datapath Optimization:** "By stripping out the instruction fetching and branch prediction needed for general computing, a TPU dedicates almost all its silicon to arithmetic logic units." — [*Source: \[Turing Award Lecture*](https://amturing.acm.org/?ref=antoinebuteau.com)*\]*
7. **On Machine Learning Workloads:** "AI workloads are highly predictable in their memory access patterns, allowing hardware to ditch complex caches in favor of software-managed scratchpads." — [*Source: \[Software Engineering Daily*](https://softwareengineeringdaily.com/?ref=antoinebuteau.com)*\]*
8. **On the Future of AI Chips:** "We are entering a phase where the algorithm dictates the silicon layout. The hardware will be as specialized as the neural networks themselves." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
9. **On Reduced Precision:** "Machine learning doesn't need 64-bit floating-point accuracy. Using 8-bit integers or bfloat16 allows us to pack drastically more compute into the same die area." — [*Source: \[Turing Award Lecture*](https://amturing.acm.org/?ref=antoinebuteau.com)*\]*
10. **On Datacenter Scale:** "The modern computer is no longer the microprocessor; the computer is the entire warehouse-scale datacenter." — [*Source: \[Computer Architecture: A Quantitative Approach*](https://store.elsevier.com/?ref=antoinebuteau.com)*\]*

### Part 6: Open Source Hardware (RISC-V)

1. **On RISC-V Origins:** "We started RISC-V at Berkeley in 2010 because we needed an instruction set for our research that didn't require signing complex licensing agreements." — [*Source: \[RISC-V Summit Keynote*](https://semiwiki.com/?ref=antoinebuteau.com)*\]*
2. **On the Open Source Model:** "RISC-V is aiming to do for hardware what Linux did for software—create a free, open standard that anyone can build upon." — [*Source: \[RISC-V International*](https://riscv.org/?ref=antoinebuteau.com)*\]*
3. **On Proprietary ISAs:** "Tying the software ecosystem to proprietary instruction sets like x86 or ARM stifles competition and locks the industry into vendor-specific hardware." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
4. **On Hardware Security:** "An open standard allows thousands of researchers to inspect the architecture for security flaws, making open hardware fundamentally more verifiable than closed silicon." — [*Source: \[Software Engineering Daily*](https://softwareengineeringdaily.com/?ref=antoinebuteau.com)*\]*
5. **On Extensibility:** "RISC-V was designed to be modular. You implement the base integer instructions, and you can add custom extensions for your specific domain without breaking compatibility." — [*Source: \[RISC-V Summit Keynote*](https://semiwiki.com/?ref=antoinebuteau.com)*\]*
6. **On Geopolitics:** "Semiconductors are a global necessity. An open standard instruction set prevents any single country or company from holding the underlying architecture hostage." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
7. **On Educational Impact:** "With RISC-V, students can actually implement a real, commercial-grade processor in an FPGA during a single semester, bridging theory and practice." — [*Source: \[Berkeley Engineering Profiles*](https://engineering.berkeley.edu/?ref=antoinebuteau.com)*\]*
8. **On Customization:** "Startups no longer have to pay millions up front for an architecture license; they can download RISC-V and immediately start customizing their silicon." — [*Source: \[RISC-V Summit Keynote*](https://semiwiki.com/?ref=antoinebuteau.com)*\]*
9. **On Avoiding Bloat:** "By keeping the base RISC-V spec frozen and small, we ensure that the architecture won't suffer from the decades of bloat that plague legacy instruction sets." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
10. **On the 50-Year Vision:** "We want RISC-V to be the universal standard for computing for the next fifty years, from embedded microcontrollers to the fastest supercomputers." — [*Source: \[RISC-V International*](https://riscv.org/?ref=antoinebuteau.com)*\]*

### Part 7: Writing, Teaching, and Communication

1. **On Writing Well:** "Failing to communicate results through clear writing and presentations is a major career detractor for researchers." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
2. **On Quantitative Evaluation:** "Computer architecture was taught as an art form based on gut feeling. John Hennessy and I wrote our textbook to make it a hard, quantitative engineering science." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
3. **On Co-Authorship:** "Finding a good co-author is like finding a good spouse. John Hennessy and I agreed on almost everything technically, which made writing the book possible." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
4. **On Reading Papers:** "A researcher should read papers critically. Don't assume the authors are right just because it was published; look for what they omitted." — [*Source: \[Advice to Graduate Students*](https://www.berkeley.edu/?ref=antoinebuteau.com)*\]*
5. **On Giving Talks:** "Your goal in a 20-minute conference talk is not to explain every equation, but to make the audience want to go read your paper." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
6. **On Textbooks:** "A textbook shouldn't just record history; it should synthesize the chaos of current research into a coherent framework for the next generation." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
7. **On Jargon:** "Avoid hiding weak ideas behind dense mathematical notation. If an idea is genuinely good, it can usually be explained simply." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
8. **On Teaching:** "Teaching undergraduate courses forces you to clarify your own understanding. If you can't explain a concept to a sophomore, you don't actually understand it." — [*Source: \[Berkeley News*](https://news.berkeley.edu/?ref=antoinebuteau.com)*\]*
9. **On Criticism:** "Active researchers must have thick skin. Peer review will tear your work apart, and your job is to extract the signal from the noise of their criticism." — [*Source: \[Advice to Graduate Students*](https://www.berkeley.edu/?ref=antoinebuteau.com)*\]*

### Part 8: Career Strategy & "Bad Careers"

1. **On Strategic Ignorance:** "Avoid 'strategic ignorance.' Failing to read the literature and subsequently reinventing a broken wheel is a surefire way to have a bad career." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
2. **On Following Trends:** "Chasing the current hot topic ensures you will always be a follower. The best research creates the new wave rather than riding the old one." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
3. **On Changing Fields:** "Don't be afraid to change your research focus every decade. Staying in one narrow subfield for a lifetime leads to diminishing returns and boredom." — [*Source: \[Computer History Museum Oral History*](https://computerhistory.org/?ref=antoinebuteau.com)*\]*
4. **On Industry vs. Academia:** "Academia lets you choose the problem; industry gives you the resources to scale the solution. Both are necessary ecosystems." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*
5. **On Burnout:** "Productivity does not always equate to crazy hours. Working to the point of burnout destroys creativity, which is your most valuable asset." — [*Source: \[Reddit Discussions on Academia*](https://www.reddit.com/r/GradSchool?ref=antoinebuteau.com)*\]*
6. **On Collaboration:** "The lone genius is mostly a myth. All the significant systems I worked on—RISC, RAID, TPU—were the result of intense team collaboration." — [*Source: TEDxNiendorf 2024*](https://www.youtube.com/watch?v=CfKogTlit58&ref=antoinebuteau.com)
7. **On Sunk Costs:** "If a research project is failing fundamentally, kill it early. Sticking with a bad idea out of stubbornness is a primary recipe for a bad career." — [*Source: \[How to Have a Bad Career in Research*](https://www.youtube.com/watch?v=1Lw9o1Qy9l8&ref=antoinebuteau.com)*\]*
8. **On Impact:** "At the end of your career, you won't count your citations. You will look at whether people actually built things differently because of your work." — [*Source: \[Turing Award Lecture*](https://amturing.acm.org/?ref=antoinebuteau.com)*\]*
9. **On Luck:** "I attribute a lot of my success to luck—being at Berkeley at the right time, meeting John Hennessy. But you have to be prepared to capitalize when luck happens." — [*Source: \[Lex Fridman Podcast #104*](https://www.youtube.com/watch?v=5FlKEEzFpkM&ref=antoinebuteau.com)*\]*