All Posts

In C, the & symbol is far more than a simple operator. It represents multiple fundamental concepts of the language: obtaining memory addresses, performing bitwise operations, and expressing logical conditions through &&. This deep dive explores every meaning of the ampersand, from pointers and pass-by-reference patterns to bit masking and embedded firmware use cases. Understanding & means understanding how C really works under the hood.

Link Time Optimization (LTO) transforms embedded firmware from separate compilation into whole-program reasoning. With Keil and armclang, it removes dead code, devirtualizes C++, reduces veneers and shortens branch distances. The result is smaller flash, fewer pipeline flushes, lower ISR latency and improved WCET predictability — measurable directly inside the map file.

SEGGER RTT (Real-Time Transfer) enables high-speed, bidirectional communication between an embedded target and a host PC using only RAM and the debug interface. It removes the need for UART, dedicated pins, and interrupts, providing high-throughput logging with minimal real-time impact. Suitable for both white-box instrumentation and black-box-like telemetry workflows, RTT enhances observability in professional embedded systems development.

I don’t come from a C++ background. I’m not a legacy systems engineer rewriting decades-old codebases. I’m not optimizing template metaprogramming or building high-frequency engines. I’m studying C++ from scratch. And instead of starting with syntax tricks or STL patterns, I started with something structural: modeling a financial instrument hierarchy. Not because of finance. But because it forces you to confront the foundations of software design.

Sharpe Is About Discipline What the Sharpe Ratio Really Measures in Trading Systems The Sharpe ratio does not measure how much a trading system makes. It measures the quality of its returns. Two strategies can reach the same profit, but only Sharpe tells you whether that result came from smooth execution or from surviving volatility and stress. Sharpe rewards consistency, not aggression.

Perry Kaufman’s Trading Systems and Methods isn’t a book you read—it’s a 1,200-page survival manual for systematic traders. No hype, no shortcuts: just trend following, mean reversion, volatility, risk management, and testing. It’s heavy, it’s brutal, and it’s the closest thing we have to a trading encyclopedia.

Heaps are the hidden heroes of computer science. They power priority queues, task schedulers, and algorithms like Dijkstra, offering O(log n) efficiency for insertions and deletions. Forget constantly sorting arrays—one simple property keeps the maximum or minimum always on top. With a few basic operations, heaps turn messy problems into elegant, high-performance solutions.

Most traders dream of beating the market. Jim Simons didn’t just beat it—he solved it. That’s literally the title of Gregory Zuckerman’s...

Your emotions suck at trading—fear, greed, and hope ruin decisions. Algorithms don’t care. They follow rules: when to enter, how to manage, when to exit. But here’s the catch: you can always hit the stop button, and that’s when psychology sneaks back in. Algo trading reduces emotions, but discipline is still the real edge.

Studying Computer Engineering, I found chemistry out of place — yet it taught me more than formulas. It built cognitive flexibility, resilience, and respect for knowledge beyond code. Tackling a tough, “irrelevant” subject became training for the real challenges of engineering: adapting, persisting, and thriving where curiosity alone isn’t enough.

D² Trading (Data-Driven Trading) is about turning markets into systems, not bets. Here algorithms replace instinct with models, backtests, and automation. Trading becomes an engineering problem: disciplined, measurable, and repeatable.

µCore₀₁ is the space where digital electronics and embedded systems come alive. From microprocessors and circuits to firmware and design hacks, this is the workbench where small cores power big ideas.

^Algo.*$ is the space where algorithms step out of textbooks and into real life. From sorting and graphs to optimization and hidden patterns in search engines, games, and markets, this is a lab for logic in action. Expect stories, code, hacks, and the messy beauty of problem-solving. If it starts with “Algo,” it belongs here.

Working on MyDLX, a clean-room implementation of a simplified DLX CPU, taught me lessons beyond exams. By treating it not just as homework but as a real design lab, I gained insight into hardware/software bridges, testing as a mindset, and the value of building systems from scratch. Extra projects like this don’t just sharpen skills — they open doors, fuel interviews, and make you stand out as an engineer.

Motivation comes and goes. When mine fades, I turn to the stories of innovators like Jobs, Einstein, and Faggin. Jobs taught vision and resilience, Einstein showed the power of persistence, and Faggin revolutionized computing with the first microprocessor. Their journeys remind me that success is not a straight path—it’s built on failures, breakthroughs, and relentless curiosity. Where do you find your motivation?