oelang

VHDL mostly lost the ASIC consumer market and for some that's the only market that matters, but the hardware design ecosystem is much bigger than that.

I wonder what AI will do to RTL/verification, the rigid nature of VHDL may be a better target for AI than Verilog.

(System)Verilog has delta cycles too you know, they call it an event queue, but it's basically the same. It's the direct variable updates that happen outside of this mechanism that cause all the issues. Imho it was a poor attempt at simulation optimization, and now you can't take it out of the language anymore.

It's important to have deterministic simulations and semantics that you can reliably reason about. Both VHDL and SystemVerilog offer this to some extent, but in the case of (System)Verilog the order of value updates is not as strictly enforced. In practice, this means that if you switch to another or a newer simulator, suddenly your testbenches will fail. The simulator vendors love this of course. This hidden cost is underestimated.

No sane hardware engineer would want randomness in their simulation unless they get to control it.

VHDL still dominates in medical, military, avionics, space etc. and it's generally considered the safer RTL language, any industry that requires functional safety seems to prefer it.

It's also the most used language for FPGA in Europe but that's probably mostly cultural.

And I wish you read the article, you're comments are completely off topic.

Jim was involved in the early versions of Zen & M1, I believe he knows.

Apples M series looks very impressive because typically, at launch, they are node ahead of the competition, so early access deals with TSMC is the secret weapon this buys them about 6 months. They also are primarily laptop chips, AMD has competitive technology but always launches the low power chips after the desktop & server parts.

AMD is already competitive on inference

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 transformer engine is a fairly recent development (april this year I think) so I don't think they're very far behind.

They have improved their software significantly in the last year, but there is a movement that's broader than AMD that wants to get rid of CUDA.

The entire industry is motivated to break the nvidia monopoly. The cloud providers, various startups & established players like intel are building their own AI solutions. Simultaneously, CUDA is rarely used directly, typically a higher level (Python) API that can target any low-level API like cuda, PTX or rocm.

What AMD is lacking right now is decent support for rocm on their customer cards on all platforms. Right now if you don't have one of these MI cards or a rx7900 & you're not running linux you're not going to have a nice time. I believe the reason for this is that they have 2 different architectures, CDNA (the MI cards) and RDNA (the customer hardware).

If you're looking for fair comparisons don't ask nVidias marketing department, those guys are worse than Intel.

What AMD did was a true comparison, while nvidia is applying their transformer engine which modifies & optimizes some of the computation to FP8 & they claim no measurable change in output. So yes, nvidia has some software tricks left up on their sleeve and that makes comparisons hard, but the fact remains that their best hardware can't match the mi300x in raw power. Given some time, AMD can apply the same software optimizations, or one of their partners will.

I think AMD will likely hold the hardware advantage for a while, nVidia doesn't have any product that uses chiplets while AMD has been developing this technology for years. If the trend continues to have these huge AI chips, AMD has a better hand to economically scale their AI chips.

> refers to scalability of the syntax

And the flexibility of the type system and the advanced type inference.

Well you're wrong, you can't run VS Code on the cloud.

There are many examples: a pci-express bus or an application optimized ddr controller or a full tcp/ip stack or a caching/prefetch system or any advanced processor with feedback .... these kinds systems require precise control.

It can be done but all the advantages of HLS are gone. The code is filled with a ton of pragmas that make the code unreadable and a lot longer than the VHDL or SV equivalent.

Register-rebalancing (other companies call it retiming) is a very old technique. You can do it with SV & VHDL, just add delays & the synthesizer will know what to do. Vivado has caught up with the solutions from Altera but there are better (more expensive) synthesizers that easily beat both, the have supported this feature for at least 15 years.