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#graph

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screwlisp

#programming #McCLIM #commonLisp #emacs #animating #graph #video.

toobnix.org/w/qAnmJAKv1mhuwem7

Silent, two minutes thirty of just what me being at a computer is like. I write a closure that has an example graph tree in it, open the frame, hand-write a tree into the interactor the frame draws, start a background loop that randomly changes between graph frames.

The code demonstrates a way of asyncronously running animations in mcclim.
Source codeberg.org/tfw/lineage-traci

Comments, thoughts(, prayers)?

PeerTube#Graph #animating #Lisp #McCLIM #Emacs #programmingBy screwtape_channel
Replied to Daniele Verducci 🧉
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Daniele Verducci 🧉
It works! I placed it in the kitchen to test it, because it's the place where #temperature and #humidity change the most. At 9:30 we opened the window to let the #cats out, and at 12:30 started preparing lunch. It's very noticeable by the temperature #graph. I wonder if I can use these temperature changes to identify what's happening (open window, cooking etc) and maybe run some #automations in #homeassistant...
Public
Hacker News

Piccolo: Large-Scale Graph Processing with Fine-Grained In-Memory Scatter-Gather

arxiv.org/abs/2503.05116

#HackerNews #Piccolo #Graph #Processing #In-Memory #ScatterGather #LargeScale #Computing

arXiv.orgPiccolo: Large-Scale Graph Processing with Fine-Grained In-Memory Scatter-GatherGraph processing requires irregular, fine-grained random access patterns incompatible with contemporary off-chip memory architecture, leading to inefficient data access. This inefficiency makes graph processing an extremely memory-bound application. Because of this, existing graph processing accelerators typically employ a graph tiling-based or processing-in-memory (PIM) approach to relieve the memory bottleneck. In the tiling-based approach, a graph is split into chunks that fit within the on-chip cache to maximize data reuse. In the PIM approach, arithmetic units are placed within memory to perform operations such as reduction or atomic addition. However, both approaches have several limitations, especially when implemented on current memory standards (i.e., DDR). Because the access granularity provided by DDR is much larger than that of the graph vertex property data, much of the bandwidth and cache capacity are wasted. PIM is meant to alleviate such issues, but it is difficult to use in conjunction with the tiling-based approach, resulting in a significant disadvantage. Furthermore, placing arithmetic units inside a memory chip is expensive, thereby supporting multiple types of operation is thought to be impractical. To address the above limitations, we present Piccolo, an end-to-end efficient graph processing accelerator with fine-grained in-memory random scatter-gather. Instead of placing expensive arithmetic units in off-chip memory, Piccolo focuses on reducing the off-chip traffic with non-arithmetic function-in-memory of random scatter-gather. To fully benefit from in-memory scatter-gather, Piccolo redesigns the cache and MHA of the accelerator such that it can enjoy both the advantage of tiling and in-memory operations. Piccolo achieves a maximum speedup of 3.28$\times$ and a geometric mean speedup of 1.62$\times$ across various and extensive benchmarks.
Public
N-gated Hacker News

Ah yes, yet another ✨open-source✨ marvel promising to revolutionize threat intelligence with a user guide longer than a Russian novel. 🔍🔍 'Cradle', because who doesn't want to be rocked to sleep by endless #dashboards and markdown editors? 🙄 Just what we needed, a hub that lets you "effortlessly" traverse relationships – perfect for those with a graph fetish. 📈🔗
cradle.sh/ #open-source #threat-intelligence #Cradle #tech-news #graph-visualization #HackerNews #ngated

cradle.shCRADLE Intelligence HubBatteries Included Threat Intelligence Collaboration
Public
Jason Beets

This graph shows how the seven most popular identity terms from 2024 have performed in each Gender Census since 2015.

We’ll explore the top five terms today.

Make sure to pay attention to the Y-axes of the line graphs in the articles in this series. Very few of them will begin at 0.

11/x

A line graph showing the results for various terms in the Gender Census from 2015 to 2024.
ALT
#nonbinary#queer#trans
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