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Joined 11 months ago
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Cake day: August 2nd, 2023

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  • And I did the same as a kid in the late 2000s in order to play World of Warcraft. Found someone’s info on a random online dump, filled it in and didn’t think more about the id theft. What I then learned is that there is NO “fake” IDs that can pass this test. It’s just plain old ID theft of actual people.

    The ID itself is encoded as 3-digit city/3-digit district/8-digit dob/and 4 random digits. There is no “generated” name that works with a specific ID since the name isn’t encoded anywhere. Most reputable vendors perform the check backed by an actual government DB.

    The problem is that it IS the exact same info used to apply for bank accounts, loans, mobile phone numbers, etc. And nobody bats an eye when a pirated gaming app asks for it. This could be legitimate, but I’m more willing to say this is someone’s ID collection scheme. If that’s the case, it could be doing more than just collecting IDs (cause why not?) or it’s at least facilitating more ID theft.






  • Some people play games to turn their brains off. Other people play them to solve a different type of problem than they do at work. I personally love optimizing, automating, and min-maxing numbers while doing the least amount of work possible. It’s relatively low-complexity (compared to the bs I put up with daily), low-stakes, and much easier to show someone else.

    Also shout-out to CDDA and FFT for having some of the worst learning curves out there along with DF. Paradox games get an honorable mention for their wiki.




  • The argument is that processing data physically “near” where the data is stored (also known as NDP, near data processing, unlike traditional architecture designs, where data is stored off-chip) is more power efficient and lower latency for a variety of reasons (interconnect complexity, pin density, lane charge rate, etc). Someone came up with a design that can do complex computations much faster than before using NDP.

    Personally, I’d say traditional Computer Architecture is not going anywhere for two reasons: first, these esoteric new architecture ideas such as NDP, SIMD (probably not esoteric anymore. GPUs and vector instructions both do this), In-network processing (where your network interface does compute) are notoriously hard to work with. It takes CS MS levels of understanding of the architecture to write a program in the P4 language (which doesn’t allow loops, recursion, etc). No matter how fast your fancy new architecture is, it’s worthless if most programmers on the job market won’t be able to work with it. Second, there’re too many foundational tools and applications that rely on traditional computer architecture. Nobody is going to port their 30-year-old stable MPI program to a new architecture every 3 years. It’s just way too costly. People want to buy new hardware, install it, compile existing code, and see big numbers go up (or down, depending on which numbers)

    I would say the future is where you have a mostly Von Newman machine with some of these fancy new toys (GPUs, Memory DIMMs with integrated co-processors, SmartNICs) as dedicated accelerators. Existing application code probably will not be modified. However, the underlying libraries will be able to detect these accelerators (e.g. GPUs, DMA engines, etc) and offload supported computations to them automatically to save CPU cycles and power. Think your standard memcpy() running on a dedicated data mover on the memory DIMM if your computer supports it. This way, your standard 9to5 programmer can still work like they used to and leave the fancy performance optimization stuff to a few experts.