It's easy to think of cryptography as a monolithic block of code, all doing the same thing, just faster or slower. But dive a little deeper, and you find a fascinating landscape of performance differences, especially when comparing standard implementations with specialized ones like BoringCrypto. I was looking at some benchmark results recently, and honestly, some of the findings were quite surprising, prompting a bit of a deep dive.
At first glance, the overhead of calling into a library like BoringCrypto via cgo seems like a predictable bottleneck. We're talking about an extra couple of hundred nanoseconds for each call. For something as granular as encrypting a single 16-byte block with AES, that jump from a mere 13 nanoseconds to over 200 nanoseconds is a staggering 1500% increase. It makes you hope that larger, bulk operations are smart enough to make that cgo call just once, rather than repeatedly for every small chunk of data.
But then there are the real head-scratchers, the things that make you pause and wonder if something's amiss. Take AES, for instance. Operations like AESCFBEncrypt1K and its decryption counterpart, along with AESOFB1K, are significantly slower. The culprit? Apparently, there's no built-in support for bulk CFB operations, no cipher.cfbAble interface. It makes you wonder if adding one would be a straightforward fix, smoothing out those rough edges.
Then there's AESCTR1K, which seems to be ignoring the ctrAble implementation that BoringCrypto's AES cipher is offering. Similarly, AESCBC encryption and decryption also appear to be bypassing the optimized implementations BoringCrypto provides. These aren't just minor blips; they suggest potential bugs or missed optimizations within the standard Go distribution itself, something that definitely warrants a closer look.
Moving over to elliptic curve digital signatures (ECDSA), things get even more intriguing. Why does signing with P256 take an extra 9 microseconds in BoringCrypto? That's too much to be attributed solely to cgo overhead. It begs the question: could the signature conversion process be improved? And the performance of P384 signing is a real eye-opener. It drops from a hefty 5.54 milliseconds to a much more manageable 0.85 milliseconds when using BoringCrypto. This suggests the standard Go implementation has a whopping six times more room for improvement! Even after that massive gain, I'm still puzzled why P384 remains so much slower than P256. It’s a puzzle that hints at deeper architectural differences or perhaps less optimized algorithms for the larger curves.
Key generation for ECDSA is another area where BoringCrypto lags significantly behind Go, being about ten times slower. This makes me wonder if the Go version is perhaps leveraging some crucial optimizations that the BoringCrypto implementation is missing. It’s a reminder that 'standard' doesn't always mean 'best' in every scenario.
And what about HMAC? The benchmark for HMACSHA256_1K in BoringCrypto taking the same amount of time as HMACSHA256_32 is peculiar. Even more so, when you compare BoringCrypto's HMACSHA256_1K (2 microseconds) to the standard crypto/sha256's Hash1K (4 microseconds), it raises questions about how these hashing algorithms are being integrated and optimized.
Interestingly, RSA2048 signing is actually faster in BoringCrypto, coming in three times quicker. This is a nice win, but it highlights the variability. Looking at the raw numbers, the differences are stark: AES encryption/decryption sees massive slowdowns via cgo, while ECDSA signing on P384 sees a dramatic speedup. It’s a complex interplay of how the underlying algorithms are implemented, how they interface with the Go runtime, and whether specific optimizations are being leveraged.
Ultimately, these performance comparisons aren't just about bragging rights for speed. They're about understanding the nuances of cryptographic implementations, identifying potential areas for improvement, and ensuring that the tools we rely on are as robust and efficient as they can be. It’s a journey of discovery, and sometimes, the most interesting findings are the ones that leave you with more questions than answers.
