Hi, to improve the service into Confiared I’m rewritting the CDN software.
We was with Nginx + Nginx FastCGI cache + PHP (to just proxy the reply). This solution lack fine cache control tuning, some bug due to Nginx cache.
Then I have rewritten the CDN as standalone FastCGI server, the cache is directly controlled by the server. If same url is already downloading, then the content is send from the partial downloaded content. I choose monothread to have great performance without thread coherency code (more simple to dev, more eficience if the code is very fast because if the code is very fast most of the time is consumed into thread management and data migration from a CPU to another CPU).
The code is specific, not flexible and generalist. I parse the protocols (DNS, FastCGI, …) on fly. That’s greatly improve the performance, reduce the memory. An internal page is served 3x more faster than a simple « Hello world » into PHP 7.4.
The future improvement are: better cache, cache some stuff where needed (DNS, …), use io_uring to improve file access and be 3x more fast than Nginx with static file, do profile to optimize the code. (And maybe do my own http server)
What is the problem with other Architecture for Linux and developer?
When you have code abstraction (as Python, Java, C#), porting is transparent then easy to support another architecture. But lot of software in the system are in C/C++, with old code, that’s mean: Each time where you have system specific or architecture specific code, you need adapt to new system/architecture. For 32Bits, in C/C++, some dirty code cast pointer to integer, that’s generate problem on 32/64 barrier, added to less popular each years then less maintained by the owner of each project, …
64Bits support is too hard than do generic support with clean code.
About obsolescence, the ARM quit 32Bits into the last 10 years. I have lot of running hardware in 32Bits. It’s fully functional, very good for the assigned task.
In this context: Every body try hard to just save few % of resources for the earth. We don’t have control on big company then forgot support the last android on 5 years phone. But generic architecture support, it easy (yes not optimized, and?) and prevent:
Manufacturing other hardware (less wast, less wars for rare resources)
Manufacturing hardware with compatibility, then more silicon, less performance
Shipping (resources and problem)
Take lot of time for person and company to buy other hardware, change it, configure it, fix for the new hardware
At performance, 32Bits on x86 it’s more slow but for the software with large pointer usage, it use less memory. And the performance is not the target to everyone.
After C10k (10 000 concurrency connections), C10M (10 000 000 concurrency connections), now C10B is near (10 Billions concurrent connections, 10Tbps, 10 billions packets per seconds, 1 billion connections/seconds). In my case: 1 Billion concurrent connections, 1Tbps, 1 billions packets per seconds, 1 millions connections/seconds)
I have test it with CatchChallenger, with 32 core Threadripper 2990WX , 256GB DDR4, Radeon RX Vega 64.
This experiment can be used for high speed network packet processing for ethernet 100G+ or infinityband device. I have do as R&D for my company router with 1Tbps (at 64B packet size) routing capability certified with benchmark.
I have do stateless filter on IPv6 input, each processing unit after do the state-full work, but with an special dispatching memory access to reduce the cache miss. Mean: IP/TCP processing GPU, CatchChallenger processing CPU.
Difficulty: Very limited into memory, I had used specialized swap technique with barer to delay some class of trafic (move on map: 95% of move, + not published protocol with another vector move to prevent memory access and only parse last pos with need to use previous data), bulk processing of this.
Result:
59ms average reply time
95% 342ms reply time
Burn 1.2Tbps of network bandwidth
because it improve lot of the compression ratio, improve the decompression speed. Then now your tiled map file .tmx can be save with zstd compression with this version.
Suite a la news de Phoronix sur Zstd 1.3.5, j’ai le plaisir de vous annoncer que grace au multiplication de 15x de la vitesse de compression de Zstd sur les petits volumes de données, CatchChallenger vas être plus rapide car c’est justement le cas typique d’utilisation de la compression.
Question: Si on est capable de de faire un objet à partir de sa photo et deviner un objet à partir de son ombre. C’est possible de reconstruire une personnalité à partir son son empreinte dans le big data?
Et donc par extension réussiter une personne en mettant sa personalité reconstituer dans un corps mécanique?
Je souhaite vous toucher 2 mots sur l’évolution du cinema dans les prochaines années.
Quel est le meilleur moyen de réaliser un film? Lire un script, vous imaginer le film, enregistrer votre représentation.
En intelligence artificiel les modèles génératifs sont là pour cela. Il permet de tout faire, sans moyen, juste avec de l’imagination. Ce qui coupe fortement les couts de production, et ce qui vas tout changer dans l’industrie du cinema. Mais particulièrement dans l’industrie des films pour adultes (tabou de société).
Je laisse juste cette note publique pour en rire ou dire que j’avais raison dans quelques années.
