A quick Chia plotting note and a future searchable tip

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2022-10-07: Updated with dual Xeon v4 bladebit.

The backlog is getting more interesting, but in an attempt to compare a Xeon Silver processor to one or two E5-2620v4 processors for some future Chia plotting, I’ve arrived at some benchmarks and a bladebit caveat for the new diskplotter.

The idea is to replace my OG plots with NFT-style plots, while still self-pooling them. At some point I will probably expand my storage again as well. 

Links are to original manufacturer specifications. If you find this document useful, feel free to send me a coffee. It might help with the memory upgrades on one or both machines too.

The systems involved:

System one:

Quick observation: On my Monoprice Stitch power meter, this system goes from about 60W at idle to 160W while plotting with Madmax or Bladebit. Not surprising, but noisy and blowy. 

System two:

Quick observation: This storage is very suboptimal for plotting, but it’s what came with the systems. I will dig into whether I have a larger faster SSD. Unfortunately this system only has USB 2.0 externally, and one low profile PCIe slot, so I’m a bit limited. Might put a 1TB NVMe drive in the PCIe slot though and see how that goes. 

Plotters:

Metrics so far:

System one, Chiapos with 12200MB memory assigned

Time for phase 1 = 10876.922 seconds. CPU (147.640%) Sun Oct 2 19:31:42 2022
Time for phase 2 = 4247.395 seconds. CPU (97.160%) Sun Oct 2 20:42:29 2022
Time for phase 3 = 9153.365 seconds. CPU (95.640%) Sun Oct 2 23:15:03 2022
Time for phase 4 = 635.266 seconds. CPU (97.980%) Sun Oct 2 23:25:38 2022

Total time = 24912.949 seconds. CPU (118.660%) Sun Oct 2 23:25:38 2022

System one, Madmax with -r 10

Phase 1 took 1461.93 sec
Phase 2 took 773.745 sec
Phase 3 took 1241.66 sec, wrote 21866600944 entries to final plot
Phase 4 took 61.6523 sec, final plot size is 108771592628 bytes
Total plot creation time was 3539.07 sec (58.9845 min)

System one, Bladebit with 16GB cache configured

Bladebit plot with 16G cache
Finished Phase 1 in 1744.37 seconds ( 29.1 minutes ).
Finished Phase 2 in 174.39 seconds ( 2.9 minutes ).
Finished Phase 3 in 1501.98 seconds ( 25.0 minutes ).
Finished plotting in 3420.74 seconds ( 57.0 minutes ).

System two with SN_750 NVMe drive (500GB), Bladebit with 24G cache

Finished Phase 1 in 1376.37 seconds ( 22.9 minutes ).
Finished Phase 2 in 148.09 seconds ( 2.5 minutes ).
Finished Phase 3 in 970.59 seconds ( 16.2 minutes ).
Finished plotting in 2495.06 seconds ( 41.6 minutes ).

 

The bladebit diskplot quirk:

If you get this error, there’s a good chance you didn’t specify the destination for the plot. 

 Allocating memory
terminate called after throwing an instance of 'std::logic_error'
what(): basic_string::Mconstruct null not valid
Aborted (core dumped)

So for example:

./bladebit -n 3 -f <farmerkey> -c <poolcontract> diskplot -t1 /nvme/tmp/ --cache 16G 

would give this error. Unlike the other plotters, it does *not* assume that your temp path is your output path if you only specify the temp path. So you’d use:

./bladebit -n 3 -f <farmerkey> -c <poolcontract> diskplot -t1 /nvme/tmp/ --cache 16G /nvme/plots/

instead. 

I will update this with further stats, and maybe make a comparison chart, as testing progresses. I’m also giving serious thought to upgrading the SSD in the dual-E5 machine. 

Obligatory disclosure:

While I work for Supermicro at the time of this writing, the servers and all other elements of my home labs and workspaces are my own and have no association with my employer. This post is my own, and my employer probably doesn’t even remember I have a blog, much less approve of it. 

Pi in the sky: Seven tips for finding the single board computer of your dreams

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2022-07-03: Updated for AtomicPi

Raspberry Pi boards have been intermittently available this year. They’re still very useful, but your odds of going into a retailer and picking up a few at list price are about as good as Ethereum hitting $5k this month. In other words, don’t hold your breath.

That being said, this type of single board computer is not completely unobtainable, even in today’s supply-chain-constrained market. Here are seven tips for finding the SBC of your dreams. 

1. Check local retailers

This is a long shot, but for some people in some regions, it may still work. My local shop, Central Computers in Silicon Valley, has had them intermittently for a couple of months at reasonable prices. 

2. Check official distributors 

You can find sellers of the Pi boards on the official Raspberry Pi website. Stock may vary from day to day, and preorders may be possible, so check early and often if you’re pursuing this option. 

3. Check Amazon

Right now, I see a number of shippable Pi 4 boards in 4GB and 8Gb on Amazon. They’re pricey, with the 4GB board around $144 and the 8GB board around $195. But if you have to have it for work, or if you’ve found a way to profit majorly from using one of these boards, it may be the way to go. 

4. Consider kits

You may be thinking “I don’t need a power supply, a microSD card, a case, and all the other stuff,” but even when backorders weren’t considered, I saw starter kits with the Pi 4 board available in quantity at the above options. Right now, my local shop has the Okdo starter kit with the 8GB board for $160, limit one per customer. The bare board is $90 but out of stock, as are all of the standalone boards. So if you need access to a board soon (hopefully with someone else footing the bill), this is a very viable option. 

5. Can I interest you in a Pi400?

The Raspberry Pi 400 computer is a Pi 4b equivalent in a different form factor. The board should have the same performance as a 4GB Pi4b, and even when boards and kits were unavailable, the Pi 400 was readily available in a standalone unit at about $80 or a kit with power adapter for $110. Prices on Amazon are a bit higher (like $120 for the standalone or $180 for the kit), but still lower than the 4GB standalone board mentioned at Amazon above.  

You won’t be able to use your Pi cases or enclosures with the Pi 400, since it’s wider, but you can consider building your own stand or looking on Thingiverse and the like for 3d-printable enclosures for these boards. 

See Jeff Geerling’s “Raspberry Pi 400 Teardown” blog post and video to see what’s inside and how you might be able to repurpose the board for your needs. 

6. Check your local marketplaces for new or used boards

You may find some boards locally on Craigslist, Facebook Marketplace, Nextdoor, or the like. eBay is also an option, but it may or may not be local. As I write this post, I see boards in my extended area from $200-325 on Craigslist, and surprisingly $120 and up on Facebook. Someone is selling a complete 8-node cluster, including 6 8GB and 2 2GB boards (and power supply, network switch, tower case, etc) for $1000, which is pretty reasonable for the current market.

With these local marketplace options, be sure to buy locally, and if possible, try the board out before paying (if it’s not sealed). With eBay, read the ad carefully and be aware of buyer protections available to you.

7. Look into other small computer options

Raspberry Pi is the most famous card-sized board, probably with the longest run and best name recognition, But you can also look at things from the RockPi boards to ODROID, to LattePanda x86.

Intel NUC (NUC5PPYB/NUC5PPYH) on a 3d-printed stand with memory and HDMI dummy plug.

You may also be able to find bare board Intel NUC systems (like the remnants of the legendary Rabbit doors from a few years ago) that, while not exactly as tiny and requiring a bit more than 3-5 watts, may well do what you need. 

See the Rabbit Overview (October 2020)
and the Rabbit Launch system build (December 2021)

For example, there are some i3 and even i7 boards here on eBay for as low as $95 shipped (searching under the “motherboard” category). When I searched under “Desktops & All-in-Ones” I found some of the old Rabbit boards (quad core Pentium with Gigabit Ethernet) for around $50 each. You’ll have to add a DDR3 SODIMM, a power supply, and probably storage of some sort, but even then you can get a 4GB system for around $100 or so. 

NVI

If you don’t need an ultra-modern OS, you can also look into systems like the Jetson Nano (which I believe easily runs Ubuntu 18), or even Jetson TK1 (Ubuntu 14/16) from NVIDIA. These outdated boards are still quite interesting, and have many uses if you can “outsource” the security to a system with a newer platform.

And yet another option I found after posting this – Digital Loggers, a Silicon Valley company better known for their Ethernet-connected power controllers (mentioned in a previous post and used in my shop) are apparently the folks behind the AtomicPi Intel Atom-based single board computer. It takes a little bit more work to power, but for $50 you get a board based on the Atom x5-Z8350 1.44GHz CPU with 2GB RAM and 16GB EMMC on board, a breakout board, and an AI camera module. 

Unlike the other boards mentioned, I have not tried this one, but it’s worth a look if you can handle the limitations and get your 5V 3A power into it yourself. 

Where do we go from here?

I’m realizing I have a few boards that may be worth dusting off and using, or even selling. There’s a Pi 3b+ cluster in need of an expansion, and some other projects in the works for the upcoming holiday weekend. 

What are you doing with single board computers, and have you found any tips and tricks I missed? Share in the comments!

Be Prepared: Personal data mining for your next job search (and some California labor law)

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As many of my readers know, I’ve been on the job search the last several months. I’ve come up with a short checklist of things to prepare as you head into the process.

Note that this is useful even if you’re not currently looking, but it may be more pressing when you are. Some of these can be digital, in the note-taking software of your choice (I lean toward Evernote), but a couple may be best in dead-tree form.

Also, with apologies to international readers, this is focused on United States concepts and constructs. Some of them may well apply outside the US, but I can’t say for sure. So I’ll bashfully hope you know your country better than I do.

And here we go.

Continue reading →

Revisiting Flexfarmer five months later – efficient Chia farming on Raspberry Pi and more

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This is another piece on a part of the Chia and cryptocurrency landscapes. See previous posts at https://rsts11.com/crypto

Back in August 2021, I wrote here about Increasing Chia farmer efficiency with Flexpool’s new FlexFarmer. I was alpha testing on Windows, Linux, and a Rock64 Pi-like computer before that, and I found that it was quite efficient, handling my 90TB farm easily on any platform without breaking a sweat, and carving around 100 watts off the power I needed to keep a dedicated farmer going.

Five months and several versions later, I wanted to come back with my experience and observations since then. I’ll also answer a couple of frequently answered questions here, for those of you who have common questions.

Disclosure: I still work for Flexpool as of this writing, but this post is based on my experience, not a press release or the pool admin’s expectations. Some of the testing I did was “on the clock” alongside support tasks, but I was not paid or asked to write this post.

Quick Flexfarmer recap

The basics are the same. With a tiny distributed binary and config file (under 10MB download) and the specifics of your PlotNFT in Chia (farmer secret key, launcher ID, payout address), at least one plot, you can start farming Chia without a fully synced node (which could save you over a week on a Pi-class machine, and at least a day or more on a more full-size PC).

Want to build a compact, inexpensive machine for farming? Read my three suggestions from a January 2022 post.

Continue reading →

Three ways to build low profile Chia (and forks) nodes

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This is another piece on a part of the Chia and cryptocurrency landscapes. See previous posts at https://rsts11.com/crypto

Need to set up a lightweight VPN to get into your low profile node remotely? Check out Stephen Foskett’s writeup on Zerotier. I’m using it on my Pi nodes to reduce NAT layers.

Many if not most Chia farmers run a full node on their farming / plotting machine. Some larger farms will use the remote harvester model, with a single full node and several machines farming plots on local storage. 

If you’re using Flexfarmer from Flexpool, or just want a supplemental node (maybe to speed up your own resyncing, or to supplement decentralization on the Chia network), you might want a dedicated node that doesn’t farm or plot. And for that use case, you don’t really need dual EPYC or AMD Threadripper machines. 

In fact, a well-planned Raspberry Pi 4B 4GB or 8GB system, with an external USB drive, will do quite well for this use. If you want to do a few forks as well, or another blockchain full node, a moderately-recent Intel NUC would do quite well for not much more. 

So here we’ll look at three builds to get you going. Note that any of these can run a full node plus Flexfarmer if you want, or just a full node. 

If you don’t already have Chia software and a full node installed, go ahead and install and sync the node on a full scale PC. it may save you five days of waiting. My original build for this use case was to test the blockchain syncing time from scratch.

Syncing from a semi-optimal Pi 4B from scratch took about 8 days, for what it’s worth. One member of the Chia public Keybase forum reported about 28 hours to sync on an Intel Core i5 12600k. 

Caveat: Raspberry Pi boards are a bit more challenging to find and even harder to find anywhere near the frequently-touted $35 price point, or even under $150. And for Chia nodes, you want a minimum of the 4GB Pi 4B (8GB wouldn’t hurt). So while it’s possible to run on older hardware, it’s not recommended.

 

You might also be able to run on a Pi400 (the Raspberry Pi 4B in a keyboard case, which is much easier to find for $100 or so, complete). I plan to test this soon.

 

Raspberry Pi with external USB SSD. 

This was my initial build, and today it’s running at the Andromedary Instinct providing an accessible full node for about 10-15 watts maximum. 

Continue reading →