amh-code
Exercism - Scala Exercises
amh-code | Exercism - Scala Exercises | |
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8 | 399 | |
551 | 7,269 | |
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10.0 | 3.5 | |
over 1 year ago | 2 months ago | |
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amh-code
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Ask HN: Recommendations for high quality, free CS books online
I recently stumbled on https://en.algorithmica.org/hpc/ which I absolutely loved. It's really well written, comprehensible and concise. It felt like a pleasure to read which I find really rare with CS textbooks and I feel like I've come out of it understanding how computers work a bit better
Does anyone have any similar CS books they'd recommend? Ideally they'd be:
- Algorithms for Modern Hardware
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Ask HN: How can I learn about performance optimization?
I admire Daniel Lemire’s work on SIMD implementations. [Lemire]
[Lemire] https://lemire.me/en/#publications
I learn a lot by reading my compiler’s and profiler’s documentation.
For Rust, the Rust Performance Book by Nicholas Nethercote et al. [Nethercote] seems like a nice place to start after reading the Cargo and rustc books.
[Nethercote] https://nnethercote.github.io/perf-book/
Algorithms for Modern Hardware by Sergey Slotin [Slotin] is a dense and approachable overview.
[Slotin] https://en.algorithmica.org/hpc/
Quantitative understanding of the underlying implementations and computer architecture has been invaluable for me. Computer architecture: a quantitative approach by John L. Hennessy and David A. Patterson [H&P] and Computer organization and design: the hardware/software interface by Patterson and Hennessy [P&H ARM, P&H RISC] are two introductory books I like the best. There are three editions of the second book: the ARM, MIPS and RISC-V editions.
[H&P] https://www.google.com/books/edition/_/cM8mDwAAQBAJ
- Algorithms for Modern Hardware – Algorithmica
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Ask HN: Programming Courses for Experienced Coders?
Hello, recently I've enjoyed Casey Muratori's Performance-Aware Programming course[0]. You could read Algorithms for Modern Hardware[1] to learn similar set of stuff though. Casey's course is aimed at bringing beginners all the way to a nearly-industry-leading understanding of performance issues while the book assumes a bit more knowledge, but I think a lot of people have trouble getting into this stuff using a book if they don't have related experience.
I've also found Hacker's Delight Second Edition[2] to be a useful reference, and I really wish that I would get around to reading What Every Programmer Should Know About Memory[3] in full, because I end up reading a bunch of other things[4] to learn stuff that's surely in there.
[0]: https://www.computerenhance.com/p/welcome-to-the-performance...
[1]: https://en.algorithmica.org/hpc/
[2]: https://github.com/lancetw/ebook-1/blob/80eccb7f59bf102586ba...
[3]: https://people.freebsd.org/~lstewart/articles/cpumemory.pdf
[4]: https://danluu.com/3c-conflict/
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SIMD Everywhere Optimization from ARM Neon to RISC-V Vector Extensions
https://en.algorithmica.org/hpc/ and http://0x80.pl/ have some stuff about this, but the latter can be dense. I've had fun getting my hands dirty with some problems at https://highload.fun/ but there's not much direction unless you go to the telegram chat and ask people questions.
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Fastest Branchless Binary Search
Other fast binary searches https://github.com/sslotin/amh-code/tree/main/binsearch
Exercism - Scala Exercises
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Developing Proficiency in Multiple Programming Languages: Part 1 - My Story
When I got my first job as a junior software engineer, my team lead suggested I take a course by MIT, Introduction to Computer Science and Programming Using Python to improve my fundamental knowledge of computer science. The course duration was 9 weeks and I learned a lot of theory about programming and picked up Python syntax. I liked the course and especially the exercises that were presented there. At that time I also discovered an amazing website called Exercism. I thought since I became familiar with the Python syntax and knew how to build simple apps, maybe it would be nice to explore some AI-related stuff. But after playing around with it I realized AI is really not for me. I'm not into analyzing data and everything that goes with it. I was more of an engineering and problem-solving type of developer.
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5 Websites to Boost Your Coding and Master Algorithms 🚀
Exercism
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MDN Curriculum
Nice, this reminds me of Exercism, which I wish was more widely known since they seem to be good folks. (disclaimer, I donate to them)
https://exercism.org/
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Do 48 Programming Challenges in 2024 #48in24
Exercism, the free programming learning platform has initiated a challenge named: 48in24.
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I learned* 12 languages in 2023: a retrospective
Last year, Exercism put together the #12in23 challenge. The goal was to learn a new programming language each month throughout the year. I was one of 135 people who completed the challenge, and I learned a lot along the way!
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12in24 - One language a month
The list of languages contains every language on Exercism, excluding ones that I've used before, web languages, or ones that I can't download for some reason.
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Ask HN: Programming Courses for Experienced Coders?
You might like https://exercism.org/
Learning by doing, with the help of mentors. Excellent way to learn a next language (as you are already familiar with the programming concepts).
- Any programs or websites to practice programming?
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Best platform for coding & programming testing everyday to improve coding skills in various language?
Exercism is pretty good for beginners with some programming language, they are open source and worth contributing to.
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Best Codewars for practice which have reflection in Web-Dev job.
Exercism
What are some alternatives?
sb_lower_bound - Fastest Branchless Binary Search
Rustlings - :crab: Small exercises to get you used to reading and writing Rust code!
branchless-binary-search - Binary search implementation that avoids branch instructions
codewars.com - Issue tracker for Codewars
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
devops-exercises - Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
tigerbeetle - The distributed financial transactions database designed for mission critical safety and performance.
Scala Exercises - The easy way to learn Scala.
ThinkingInSimd - An essay comparing performance implications of ignoring AVX acceleration
Demos and Examples in Scala (Chinese) - scala、spark使用过程中,各种测试用例以及相关资料整理
std-simd - std::experimental::simd for GCC [ISO/IEC TS 19570:2018]
interviews - Everything you need to know to get the job.