AMD announces the Spartan UltraScale+ FPGA family

I think the issue is there are different market drivers at play. GPUs are more 'visible' than FPGAs to consumers; there's probably a couple of orders of magnitude more people pushing for open source/hackable drivers for GPUs than FPGAs (at least today). So AMD doesn't feel the pressure in the FPGA market, and it's 'easier' to maintain the status quo. I suspect we'll have to wait for a use case where somewhere near as many average users are actually thinking about their FPGA vendor as they do about their GPU vendor before things will change. Maybe an AI/ML application?

Yes they are.

If you know your product needs these features you can do early prototyping and development on similar or higher end platforms and then switch to this new platform when it becomes available.

Having knowledge of upcoming parts is important in hardware engineering for planning purposes.

When you need to decide on what FPGA line you are going to base your products on, you certainly want to know years in advance what new models will obsolete your FPGA products. However, you don't just want to know their specifications but also their price.

Oh, yes. Hardware products and projects, specially those complex enough to need an FPGA, will usually have a long development pipeline and even one year seems pretty short.

And you can very often prototype with either an overpowered development board or you own prototype board with another FPGA, and then downsize appropriately as the project advances. Most importantly, if you know there will be a viable version in a year, you can postpone the final decision and Xilinx get to avoid having you choosing Altera now if it's possible that their new offering will match your project.

Stuff with a lot of simultaneous i/o that needs to be processed simultaneously, is one answer.

https://www.intel.com/content/www/us/en/healthcare-it/produc...

They enable a lot of crazy defence products. A well known german product for example is the Iris-T from Diehl Defence. Highly accurate and exceptional engineering. But I guess FPGAs are in most defence products nowadays. I think the biggest reason is that you can build/verify your own hardware without having to go through the expensive ASIC manufacturing

Edit: I just realized that these are some literal killer apps. That wasn't even intentional, lol.

- ASIC emulation and prototyping

- High-frequency trading (executed in-fabric)

- Niche real-time video devices, etc.

- Cryptocurrency mining

- Real-time motor pulse generation for robotics

- Custom NICs and HPC devices

- RF signals processing (radar, guidance, etc.)

Lower-volume specialty chips for interfaces (lots of I/O pins), such as adapters for an odd interface, custom hardware designs for which there isn't an existing chip, etc.

For instance, audio, video or other signal processing can be done by putting the algorithm "directly" into the hardware design; it will run at a constant predictable speed thereafter.

Ultra-accurate classic computer and videogame emulators!

They're used in places that require real time processing (DSP) of raw digital signals at very high (several hundred Mhz and more), where you cannot afford to miss a sample because of latency from a microcontroller (uC). I think even some PCI devices use them for this reason, and it allows you to update firmware whereas ASIC doesn't

A while back I wrote an entire FPGA pipeline to recalibrate signals from optical sensors before they were passed on to the CPU. Doing this allowed us to keep up processing speed with acquisition, so it was real time. A lot of FIR filters and FFTs. But my proudest achievement was a linear interpolation algorithm which is fairly high level and tricky to implement on FPGA, which is more geared towards simpler DSP algorithms like FIR filters, and FFT (not simpler but so much effort has got into making IPs it effectively is because you don't have to implement it yourself)

But other than that, for raw bulk compute GPUs are kicking their butts in most domains.

Any sensor that captures a ton of data that needs realtime processing to 'compress' the data before the data can be forwarded to data accumulator. Think MRI or CT scanners but industrially there are thousands of applications.

If you need a lot of realtime processing to drive motors (think industrial robots of all kinds), FPGAs are preferred of micro-controllers.

All kinds of industrial sorting systems are driven by fpgas because the moment of measurement (typically with a camera) & the sorting decision are less than a milisecond apart.

There are many more, it's a very 'industrial' product nowadays, but sometimes an FPGA will pop up in a high-end smartphone or TV because they allow to add certain features late in the design cycle.

The core of modern oscilloscopes is often an FPGA that reads out the analog-to-digital converters at ~gigasamples/s and dumps the result into a RAM chip. Some companies (Keysight, Siglent) use custom chips for this, but FPGAs are very common.

Anything where you wish you could have an ASIC but you don't have the budget for custom ASIC, and where using smaller chips either makes for worse Bill of Materials or takes up more space.

They are used everywhere, including some very small ones I've seen used purely for power sequencing on motherboards - usually very small FPGA with embedded memory that "boots" first on standby voltage and contains simple combinatoric logic that controls how other devices on motherboard are getting powered up faster than any MCU can do it - while taking less space than discrete components.

Glue logic, custom I/O systems (including high-end backplanes in complex systems), custom devices (often combined with "hard" components in the chip, like ARM CPUs in Zynq series FPGA), specialized filters that can be runtime updated.

Lots of uses.

Given the importance of Storage and Networking when working with big data for LLM. Having storage and network code in FPGA might be useful..

Some older video game consoles have been "emulated" in FPGA. You just map out the circuitry of a device and voila you get native performance without the bugs of a software implementation.

They enable a bunch of niches (some of which do have a large impact), as opposed to having a few high-volume uses. Basically anything where you really need an ASIC but you don't have the volume to justify an ASIC (and also have the requires large margins for such a product to be viable). Custom RF protocols, the ASIC development process itself, super-low-latency but complex control loops in big motor drives, that kind of thing. You'll almost never see them in consumer products (outside of maybe some super-tiny ones which aren't useful for compute but just do 'glue logic') because they're so expensive.

Low-latency (e.g. less than 20 lines) Videoswitchers/mixers. There's a huge amount of data (12Gbps for 4K/UHD) per input, with many inputs and outputs, all with extremely tight timing tolerances. If you loosen the latency restrictions you can do a small numbers of inputs on regular PCs (see OBS Studio), but at some point a PC architecture will not scale easily anymore and it is much more efficient to just use FPGAs that will do the required logic in hardware. It's such a small market that for most devices an ASIC is not a option.

Broadly speaking anything that does either a lot of reasonably specialized logic and medium-to-high performance broad work will have an FPGA in it (unless its made in very high volumes in which case it may be an ASIC, ditto for very high performance things).

Some FPGAs are absolutely tiny e.g. you might just use it as a fancy way of turning a stream of bits into something in parallel for a custom bit of hardware you have, other FPGAs are truly enormous and might be used for making a semi-custom CPU so you can do low latency signal processing or high frequency trading and so on.

I think low latency is the main thing. In most cases, to get an FPGA that's faster in terms of compute than a GPU/CPU you're going to have to spend probably hundreds of thousands (which the military do, e.g. for radar and that sort of thing).

But even a very cheap FPGA will beat any CPU/GPU on latency.

SDR

It can be of use in anything that handles a lot of data throughput but not built in large enough numbers to justify producing an ASIC. First example that comes to mind is an oscilloscope, but by definition FPGAs can be used anywhere (from retrogame consoles to radars).

I think we’re going to see a greatly increased use of FPGAs in AI applications. They can be very good at matrix multiplication. Think about an AI layer that tunes the FPGA based on incoming model requirements? Need an LPU like groq? Done. I would bet Apple Silicon gets some sort of FPGA in the neural engine.

To give you an example, these are often used in CNC machines.

Before you had to have:

A. a PLC that ran logic with real time guarantees to tie everything together. The PLC is often user-modified to add more logic.

B. Decoders that processed several mhz encoder feedback signals, somewhere between 3 and 10 of these.

C. Something that decides what to do with the data in B

D. Encoders and motor driving, also being output at several mhz (somewhere between 3 and 10 of these as well)

Among other tasks.

These were all separate chips/boards/things that you tried to synchronize/manage. Latency could be high. But if you are moving 1200 inches per minute (easy), 100 milliseconds latency is equivalent to losing track of things for 2 inches. Enough to ruin anything being made.

Nowadays it is often just an FPGA hooked up to a host core.

(or at a minimum, a time-synchronized bus like ethercat)

One particular use of FPGAs (and ASICs) is operating on bit-oriented rather than byte-oriented data. Certain kinds of compression and encryption algorithms can be implemented much more efficiently on custom chips. These are generally limited to niche applications, though, because the dominance of byte-oriented general-purpose CPUs and microcontrollers selected against such algorithms for more common applications.

Military Radar and Sonar

Deterministic latency so you know the upper bound and lower bound

They are useful for products which do video encoding, decoding, and microwave receive and transmit of video data. They are useful for TCP/IP insertion and extraction of packet data, e.g., in video streams.

Products with PCIe (PCI Express) and high speed interfaces like 10G Ethernet, SATA, HDMI, USB 3.0 and higher, Thunderbolt.

Most of the ASICs with these SerDes interfaces are not for sale on the open market, only for OEM who buy MOQ of millions.

Take for example the Raspberry PI SBCs. The Raspberry Pi only got PCIe very late (compute model 4), influencer Jeff unlocked them with a lot of difficulty https://pipci.jeffgeerling.com but you still can't buy these cheap microprocessors from Broadcom.

The reason is that no cheap PCIe chips are available for hobbyists and small company buyers (below a million dollars).

'Cheap' FPGA's starting at $200+ where and still are the only PCIe devices for sale to anyone. If you want to nitpick, a few low speed Serdes are available in $27 ECP5 FPGA's, but no 10 Gbps and higher.

Another example, I sell $130 switches with 100 Gbps switching speeds and PCIe 4x8 and QSFP28 optics. But you can't buy the AWS/Amazon ASIC chips on this board anywhere, nor their competitors chips from Broadcom, Intel, MicroSemi/Microchip, Marvell.

I went as high as Intel's vice president and also their highest level account manager VPs and still got no answer on how to buy their ASIC switches or FPGAs.

In the past, I’d have tried to use Achronix’s FPGA’s for secure processors like Burroughs B5000, Sandia Secure Processor, SAFE architecture, or CHERI. One could also build I/O processors with advanced IOMMU’s, crypto, etc. Following trusted/untrusted pattern, I’d put as much non-security-critical processing as possible into x86 or ARM chips with secure cores handling what had to be secure.

High-risk operations could run the most critical stuff on these CPU’s. That would reduce the security effort from who knows how many person-years to basically spending more per unit and recompiling. Using lean, fast software would reduce the performance gap a bit.

CHERI is now shipping in ASIC’s, works with CPU’s that fit in affordable FPGA’s, and so this idea could happen again.

From a consumer-facing perspective, FPGAs have enabled a golden age of reasonably affordable and upgradeable hardware for relatively niche tech hobbies.

* Replacement parts for vintage computers * Flash cartridges and optical drive emulators for older video game consoles * High-speed, high quality analog video upscalers

Many of these things aren't produced at a scale where producing bespoke chips is not really viable. Using an FPGA lets you build your product with off the shelf parts, and lets you squish bugs in the field with a firmware update.

There is also MiSTer, an open source project to re-implement a wide range of vintage computer hardware on the Terasic DE10-Nano FPGA.

Finally, I waited years for this. I could only use the Kitex line. Big question is will these Spartan Ultrascale+ with tranceivers and PCIe 4.0 be cheaper or more expensive?

They already supported this line rate though, for years?

What am i missing?

(IE It's still only pcie gen3, and this announcement doesn't change that)

Forgive my ignorance, and I made a brief attempt to answer it myself - what's GTH in this context?

You mean something like this: https://www.amd.com/en/products/system-on-modules/kria.html

Spartan is the glue-logic family for applications that either do not require any kind of CPU core at all or where some simple soft-core (MicorBlaze, x51, hand crafted state machine...) suffices.

Why? They have a different line for that. Not worth wasting expensive silicone die area for something a lot of customers or projects won't need.

> No hard core is a bummer.

The Zynq product family already exists.

An FPGA is a blank slate, more so than a CPU is, the programming interface is whatever the user wants to implement (including ring buffers and DMA or whatever).

In FPGAs you are literally programming the enablement of individual logic gates. That's it.

There is no DMA or command ring, you have to implement it yourself.

The FPGA bit code itself is extremely propertiary to each vendor as the nature of controlling all the logic sauces is all secret sauce. So you have to use the vendors tooling.

> I wonder what is the hardware programming interface.

Vivado

> Then quickly getting up and running a shmol RV64 core... and I guess this is hacker paradise.

https://github.com/SpinalHDL/NaxRiscv

MiSTer is about 110K , this can go up to 218K. Probably this new FPGA is something like BGA package, since it has over 500 I/O pins. Also not available this year: "AMD Spartan UltraScale+ samples and evaluation kits are expected to be available for sampling and evaluation in the first half of 2025."

You don't seem to get PCIe Gen 5 outside of the top-end devices it seems. Agilex 7 has it on the Intel side with the R-Tile devices (including a hard CXL IP too which is lovely), but their recently announced Agilex 5 (the UltraScale+ competitor) only host PCIe 4.0 x8. I guess it takes up too much in terms of resources to double the throughput on a low-power device.