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Cake day: July 8th, 2023

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  • In this section, the narrator explores the peculiarities of how cities are defined in the UK. Unlike other countries where city status is typically determined by population or government structure, Britain has its own unique criteria. The list of officially recognized cities in the UK includes some surprising and seemingly unworthy contenders, while notable places like London, Reading, and Northampton are mysteriously absent. Contrary to popular misconceptions, having a cathedral or a university does not necessarily confer city status. Instead, city status in Britain is granted by the monarch through personal command and letters patent. This tradition dates back to the 10th century and is the sole determinant of whether a place is officially classified as a city. The misconception that cathedrals play a role in city status stems from the historical significance of powerful church centers in small settlements. However, in the 19th century, as towns grew due to the Industrial Revolution, the rules were changed, and places like Birmingham gained city status based on their industrial importance rather than religious institutions. Overall, the criteria for city status in Britain are distinct and can be attributed solely to the monarch’s decision. 00:05:00 In this section, the narrator discusses the inconsistencies in the list of British cities and how some cities have lost their city status. The merging of Rochester with its neighbors in 1998 inadvertently removed it from the official list of British cities. However, the opportunity to regain city status came in 2000 when the government allowed towns to bid for it. Many towns submitted bids, with Reading being the favorite to win. Ultimately, three new cities were added to the list: Brighton, Hove, and Inverness. The narrator questions the advantages of being a city instead of a town, as the benefits seem minimal. The bidding process seems to benefit the government in terms of positive PR without requiring much commitment. 00:10:00 In this section, the speaker questions the government’s authority to change the definition of a city and suggests that perhaps it’s time to abandon this system altogether and replace it with something more meaningful. However, the speaker recognizes that the government has more pressing matters to address and doubts that redefining the definition of a city will be a priority. The speaker concludes that this tradition, filled with pomp, ceremony, and a bit of royalty, is a quintessentially British thing that adds to the country’s charm, and it’s unlikely to change anytime soon. The speaker humorously predicts that at the current rate, every corner of the country will become a city by the year 3000.


  • Intel unveiled its first direct mesh-to-mesh photonic fabric at the Hot Chips 2023 chip conference, highlighting its progress towards a future of optical chip-to-chip interconnects that are also championed by the likes of Nvidia and Ayar Labs. However, the eight-core 528-thread chip that Intel used for the demonstration stole the spotlight due to its unique architecture that sports 66 threads per core to enable up to 1TBs of data throughput. Surprisingly, the chip consumes only 75W of power, with 60 of the power being used by the optical interconnects, but the design could eventually enable systems with two million cores to be directly connected with under 400ns latency. Intels PUMA Programmable Unified Memory Architecture chip is part of the DARPA HIVE program that focuses on improving performance in petabyte-scale graph analytics work to unlock a 1000X improvement in performance-per-watt in hyper-sparse workloads. Surprisingly for an x86-centric company like Intel, the test chip utilizes a custom RISC architecture for streamlined performance in graph analytics workloads, delivering an 8X improvement in single-threaded performance. The chip is also created using TSMCs 7nm process, not Intels own internal nodes. After characterizing the target workloads, Intel concluded that it needed to craft an architecture that solved the challenges associated with extreme stress on the memory subsystem, deep pipelines, branch predictors, and out-of-order logic created by the workload. Intels custom core employs extreme parallelism to the tune of 66 hardware threads for each of the eight cores, large L1 instruction and data caches, and 4MB of scratchpad SRAM per core. The eight-core chip features 32 optical IO ports that operate at 32 GBsdir apiece, thus totaling 1TBs of total bandwidth. The chips drop into an eight-socket OCP server sled, offering up to 16 TBs of total optical throughput for the system, and each chip is fed by 32GB of custom DDR5-4000 DRAM. Intel fabbed the chip on TSMCs 7nm process with 27. 6 billion transistors spanning a 316mm2 die. The eight cores, which consume 1. 2 billion transistors, run down the center of the die, flanked by eight custom memory controllers with an 8-byte access granularity.













  • silicon is really inefficient: too much power wasted in form of heat (Joule effect), on the other hand, quantum computing functions in absolute zero conditions, so no inefficiencies. in a perfect world, one would outsource all its calculations to a quantum instance, but the thing is too costly and centralized; if everyone could afford low latency internet our phones wouldn’t require cpus and gpus, instead we could run them on a quantum computer, but since its too centralized, the issue of privacy would prevail. Would be nice if we had quantum instances scattered around, like lemmy instances, but donations won’t probably cut it to cover costs, so we r stuck with sand computers for now



  • the video explores different processing units used in computers. GPUs are essential for tasks like rendering graphics and training deep learning models. TPUs, on the other hand, are designed specifically for tensor operations required in deep learning and can save significant time and cost when training models. DPUs, or data processing units, are optimized for moving and processing large amounts of data in Big Data Centers, relieving the CPU from such tasks. Finally, there is the potential for the development of QPUs, or quantum processing units, which operate using qubits instead of classical bits and have the potential to revolutionize computing with their ability to handle complex algorithms exponentially faster. However, the threat they pose to encryption and security is also a concern.


  • i had a tab s2 with 28nm soc, 3gig lpddr3 ram running android 7 and the app quickly crashes, now i use an infinix (random asian brand, but way better than the rest) with a 12nm soc 4 gig of ram (4 doesnt seem enough) and 10w slow charging, the next phone i consider buying would run android 13 with 16 gig of ram (swap included, well, unlocked at least), also includes 33w fast charging and a 6nm soc, kinda finding myself reasons to upgrade, but as u said i am waiting this out too: i wanted to run the app on my pc but also i would have to upgrade my laptop ram so my os could support the android emulator without hiccups. i considered running my own instance for this sake but kinda extreme…lemmy is addictive not gonna lie