ASIC Boincing Dead?

[Megacruncher]

Recovering from my Rip Van Wnkle style epic stupor, one of the most obvious changes is that it looks like we are all back on good old honest CPU & GPU crunching with evil cheating ASIC nowhere to be found.
Is that an accurate perception?
And what have people done with their miners?
Are they worth selling or should I start mining bitcoins, which some sources suggest is now worthwhile, whereas a couple of years ago you'd have been hard pushed to cover the cost of the electricity.

[scole of TSBT]

There's not any Boinc projects using the ASICs. Gridcoin is paying it's team members a pittance to crunch for them and a couple other projects appear to be gearing up to reward crunchers in crypto currency. To figure out whether it's worth while to mine bitcoin or some other sha-256 crypto currency, find a website like What to mine, plug in the hash rate, power consumption of your whole rig and lecky rate and it will show you what the current profit or loss is for mining various currencies.

[Alez]

I sold all mine on ebay and converted them into newish nVidea cards, 970 and 980's. I then sold most of the older AMD cards and again converted that into more nVidea 970 and 980's. Much more crunching power with less heat and lecky. Also easy to set up on Lubuntu linux. I have a few more cards that I need to sell on as round two of the revamp, plus a few 7970's that I really should move on to.
The miners all sold no problem, so I guess there is still a market in the UK for mining Bitcoin. The only ones I have left were the old butterfly rigs which were too heavy and underpowered to make it worthwhile selling them. They are gathering dust incase another ASIC project comes along, but in reality, they are only useful as door stops.

[Dirk Broer]

I am glad I only invested into USB-stick miners....
I do hope some geek will make a Seti@Home ASIC or so in the future though.

[Dirk Broer]

AI (artificial Intelligence) and ML (Machine Learning) are quite big in IT nowadays and can be found on various hardware platforms.
But what are these DPUs, IPUs, NPUs, QPUs, TPUs and VPUs, and what are they good for in BOINC?

TL, DR: No, they don't work with BOINC -yet.

DPU
DPUs, or data processing units, are a new class of programmable processors and will join CPUs and GPUs as one of the three pillars of computing. DPUs can be used as stand-alone embedded processors, but are more often incorporated into SmartNICs, network interface controllers used as critical components in a next-generation servers. You won't find them in your ARM or RISC-V based SBCs yet, nor in your x86-64 PC, but perhaps in your (dedicated AI) server

IPU
IPUs, Intelligence Processing Units, are highly flexible, easy-to-use highly parallel processors designed from the ground up for AI workload. But it is in fact a vendor-specific NPU, mainly known by GraphCore products. You won't find them in your ARM or RISC-V based SBCs, or in your x86-64 PC or server yet either.

NPU
NPUs, in the meaning of Neural Processing Unit, are AI accelerators. It is a specialized hardware accelerator designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and machine vision. NPUs sometimes go by similar names such as a tensor processing unit (TPU), neural network processor (NNP) and intelligence processing unit (IPU) as well as vision processing unit (VPU) and graph processing unit (GPU).
There are a lot of new SBCs that have a NPU within the SOC they are based on as e.g. the Amlogic A311D, or the Rockchip RK3399Pro, RK3566, RK3568 and RK3588. Other boards have an extra NPU, such as the Orange Pi 4B (a Gyrfalcon Lightspeeur 2801S).

QPU
QPUs, Quantum Processing Units, are physical chips that contain a number of interconnected qubits. They are foundational components of a full quantum computer, a whole different ball game.
They are the future of High Performance Computing, and hopefully of BOINC too -but in that case the far future.

TPU
TPUs, Tensor Processing Units, are AI accelerator application-specific integrated circuits (ASICs) developed by Google specifically for their neural network machines. But it is in fact again a vendor-specific NPU. There are complete SBCs with a Google TPU in them: the Google Coral Dev Boards and the ASUS Tinker Edge T. You can also buy them as USB stick accelerator, or in mini PCIe or M.2 format for in your x86-64 PC or server.

VPU
VPUs, Vision Processing Units, are a class of microprocessors. It is a specific type of AI accelerator, designed to accelerate machine vision tasks. The Intel Movidius Neural Compute USB Sticks NCS and NCS2 are examples.
They too are in fact vendor-specific NPUs.