This is the next public key (#110, with a private key in range [ 2^109 , 2^110 - 1], 109 bit) they have been looking for over 7,5 months (about 225 days):
0309976ba5570966bf889196b7fdf5a0f9a1e9ab340556ec29f8bb60599616167d
(address: 12JzYkkN76xkwvcPT6AWKZtGX6w2LAgsJg)
The Pollard's kangaroo ECDLP solver needs 2*(2^(109/2)) = 2^55.5 steps to retrieve this private key, a GPU that computes 2^30 steps/sec would take 2^25.5 seconds, about 550 days.
0309976ba5570966bf889196b7fdf5a0f9a1e9ab340556ec29f8bb60599616167d
(address: 12JzYkkN76xkwvcPT6AWKZtGX6w2LAgsJg)
The Pollard's kangaroo ECDLP solver needs 2*(2^(109/2)) = 2^55.5 steps to retrieve this private key, a GPU that computes 2^30 steps/sec would take 2^25.5 seconds, about 550 days.
Based solely on the tests I’ve done so far with RTX 2080 Tis, it’s reasonable to expect that a 110-bit interval can be solved in 5 days, 7 hours, and 39 minutes on average with 128 RTX 2080 Tis. While consuming ~640GB(~80bytes/point in the hash table) of distinguished points storage with a 23-bit points mask. Also, one might get very lucky and solve it less than the average time, say a couple of days, or 18-19 days worst case. But we definitely can reduce the memory requirements by only using 4-bytes for herd type, 8-bytes for the x-coordinate, and 16-bytes for starting position of the kangaroo. When there’s a collision, we re-walk the kangaroo’s path up to the distinguished point and check for a solution.
