alt Hacker News> Heracles, which sped up FHE computing tasks as much as 5,000-fold compared to a top-of the-line Intel server CPU.
That is nice speed-up compared to generic hardware but everyone probably wants to know how much slower it is than performing same operations on plain text data? I am sure 50% penalty is acceptable, 95% is probably not.
Replies
Current FHE on general CPUs is typically 10,000x to 100,000x slower than plaintext, depending on the scheme and operation. So even with a 5,000x ASIC speedup you are still looking at roughly 20-100x overhead vs unencrypted compute.
That rules out anything latency-sensitive, but for batch workloads like aggregating encrypted medical records or running simple ML inference on private data it starts to become practical. The real unlock is not raw speed parity but getting FHE fast enough that you can justify the privacy tradeoff for specific regulated workloads.
There are applications that are currently doing this without hardware support and accepting much worse than 95% performance loss to do so.
This hardware won’t make the technique attractive for ALL computation. But, it could dramatically increase the range of applications.