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Author Topic: == Bitcoin challenge transaction: ~1000 BTC total bounty to solvers! ==UPDATED==  (Read 47247 times)
This is a self-moderated topic. If you do not want to be moderated by the person who started this topic, create a new topic. (11 posts by 1+ user deleted.)
zielar (OP)
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January 19, 2020, 07:08:13 PM
Last edit: May 16, 2023, 07:32:18 AM by zielar
Merited by Jean_Luc (10), LoyceV (6), Welsh (2), dragonvslinux (1)
 #1

This is a continuation of the popular "32BTC puzzle" - https://bitcointalk.org/index.php?topic=1306983.0 and https://bitcointalk.org/index.php?topic=5166284 - with the inclusion of the latest data updated.


Quote
2015-01-15 - a transaction was created in blockchain (included in block 339085) containing a transfer transaction for 256 different Bitcoin addresses: https://blockchain.info/tx/08389f34c98c606322740c0be6a7125d9860bb8d5cb182c02f98461e5fa6cd15

2017-07-11 - funds from addresses 161-256 were moved to the same number of addresses of the lower range - thus increasing the amount of funds on them. This takes place in block 475240: https://www.blockchain.com/btc/tx/5d45587cfd1d5b0fb826805541da7d94c61fe432259e68ee26f4a04544384164

2019-05-31 - the creator of the "puzzles" creates outgoing transactions with the value of 1satoshi for addresses #65, #70, #75, #80, #85, #90, #95, #100, #105, #110, #115 , #120, #125, #130, #135, #140, #145, #150, #155, #160 with the aim of probably comparing the difficulty of finding a private key for the address from which such a transaction was carried out, and one that There is no transaction.

2023-04-16 - The creator of the challenge paid rounded amounts of BTC to the remaining unguessed addresses - thus increasing the value of the prizes by a total of over 900 BTC. From this moment, for example - the reward value for address 66 is not 0.66BTC but 6.6BTC
Quote
First output: take random number from 20 upto 21-1, use it as private key
Second output: take random number from 21 upto 22-1, use it as private key
Third output: take random number from 22 upto 23-1, use it as private key

The outputs relate to transactions from 2015 in which the transaction was performed for all 256 addresses.

You can check them: ==> http://bit.do/maintx <==

Quote

Useful websites for challengers:

If you want - you can send me a donation to my BTC wallet address 31hgbukdkehcuxcedchkdbsrygegyefbvd
zielar (OP)
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January 19, 2020, 07:13:32 PM
Last edit: September 11, 2022, 12:14:22 PM by zielar
Merited by BurtW (5), LoyceV (4), NotATether (3), ImThour (3), vapourminer (2), Welsh (2), Halab (2), PrimeNumber7 (1)
 #2

Code:
No. |=========PRIVATE KEY IN HEX (if it was found and known)========== |===========WALLET ADDRESS===========| ===============UPPER RANGE LIMIT================ | ===================COMPRESSED PUBLIC KEY IN HEX=================== | ==SOLVED DATE==
01  | 0000000000000000000000000000000000000000000000000000000000000001 | 1BgGZ9tcN4rm9KBzDn7KprQz87SZ26SAMH | 1                                                | 0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798 | 2015-01-15
02  | 0000000000000000000000000000000000000000000000000000000000000003 | 1CUNEBjYrCn2y1SdiUMohaKUi4wpP326Lb | 3                                                | 02f9308a019258c31049344f85f89d5229b531c845836f99b08601f113bce036f9 | 2015-01-15
03  | 0000000000000000000000000000000000000000000000000000000000000007 | 19ZewH8Kk1PDbSNdJ97FP4EiCjTRaZMZQA | 7                                                | 025cbdf0646e5db4eaa398f365f2ea7a0e3d419b7e0330e39ce92bddedcac4f9bc | 2015-01-15
04  | 0000000000000000000000000000000000000000000000000000000000000008 | 1EhqbyUMvvs7BfL8goY6qcPbD6YKfPqb7e | 15                                               | 022f01e5e15cca351daff3843fb70f3c2f0a1bdd05e5af888a67784ef3e10a2a01 | 2015-01-15
05  | 0000000000000000000000000000000000000000000000000000000000000015 | 1E6NuFjCi27W5zoXg8TRdcSRq84zJeBW3k | 31                                               | 02352bbf4a4cdd12564f93fa332ce333301d9ad40271f8107181340aef25be59d5 | 2015-01-15
06  | 0000000000000000000000000000000000000000000000000000000000000031 | 1PitScNLyp2HCygzadCh7FveTnfmpPbfp8 | 63                                               | 03f2dac991cc4ce4b9ea44887e5c7c0bce58c80074ab9d4dbaeb28531b7739f530 | 2015-01-15
07  | 000000000000000000000000000000000000000000000000000000000000004C | 1McVt1vMtCC7yn5b9wgX1833yCcLXzueeC | 127                                              | 0296516a8f65774275278d0d7420a88df0ac44bd64c7bae07c3fe397c5b3300b23 | 2015-01-15
08  | 00000000000000000000000000000000000000000000000000000000000000E0 | 1M92tSqNmQLYw33fuBvjmeadirh1ysMBxK | 255                                              | 0308bc89c2f919ed158885c35600844d49890905c79b357322609c45706ce6b514 | 2015-01-15
09  | 00000000000000000000000000000000000000000000000000000000000001D3 | 1CQFwcjw1dwhtkVWBttNLDtqL7ivBonGPV | 511                                              | 0243601d61c836387485e9514ab5c8924dd2cfd466af34ac95002727e1659d60f7 | 2015-01-15
10  | 0000000000000000000000000000000000000000000000000000000000000202 | 1LeBZP5QCwwgXRtmVUvTVrraqPUokyLHqe | 1023                                             | 03a7a4c30291ac1db24b4ab00c442aa832f7794b5a0959bec6e8d7fee802289dcd | 2015-01-15
11  | 0000000000000000000000000000000000000000000000000000000000000483 | 1PgQVLmst3Z314JrQn5TNiys8Hc38TcXJu | 2047                                             | 038b05b0603abd75b0c57489e451f811e1afe54a8715045cdf4888333f3ebc6e8b | 2015-01-15
12  | 0000000000000000000000000000000000000000000000000000000000000A7B | 1DBaumZxUkM4qMQRt2LVWyFJq5kDtSZQot | 4095                                             | 038b00fcbfc1a203f44bf123fc7f4c91c10a85c8eae9187f9d22242b4600ce781c | 2015-01-15
13  | 0000000000000000000000000000000000000000000000000000000000001460 | 1Pie8JkxBT6MGPz9Nvi3fsPkr2D8q3GBc1 | 8191                                             | 03aadaaab1db8d5d450b511789c37e7cfeb0eb8b3e61a57a34166c5edc9a4b869d | 2015-01-15
14  | 0000000000000000000000000000000000000000000000000000000000002930 | 1ErZWg5cFCe4Vw5BzgfzB74VNLaXEiEkhk | 16383                                            | 03b4f1de58b8b41afe9fd4e5ffbdafaeab86c5db4769c15d6e6011ae7351e54759 | 2015-01-15
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16  | 000000000000000000000000000000000000000000000000000000000000C936 | 1BDyrQ6WoF8VN3g9SAS1iKZcPzFfnDVieY | 65535                                            | 029d8c5d35231d75eb87fd2c5f05f65281ed9573dc41853288c62ee94eb2590b7a | 2015-01-15
17  | 000000000000000000000000000000000000000000000000000000000001764F | 1HduPEXZRdG26SUT5Yk83mLkPyjnZuJ7Bm | 131071                                           | 033f688bae8321b8e02b7e6c0a55c2515fb25ab97d85fda842449f7bfa04e128c3 | 2015-01-15
18  | 000000000000000000000000000000000000000000000000000000000003080D | 1GnNTmTVLZiqQfLbAdp9DVdicEnB5GoERE | 262143                                           | 020ce4a3291b19d2e1a7bf73ee87d30a6bdbc72b20771e7dfff40d0db755cd4af1 | 2015-01-15
19  | 000000000000000000000000000000000000000000000000000000000005749F | 1NWmZRpHH4XSPwsW6dsS3nrNWfL1yrJj4w | 524287                                           | 0385663c8b2f90659e1ccab201694f4f8ec24b3749cfe5030c7c3646a709408e19 | 2015-01-15
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23  | 0000000000000000000000000000000000000000000000000000000000556E52 | 1L2GM8eE7mJWLdo3HZS6su1832NX2txaac | 8388607                                          | 03f82710361b8b81bdedb16994f30c80db522450a93e8e87eeb07f7903cf28d04b | 2015-01-15
24  | 0000000000000000000000000000000000000000000000000000000000DC2A04 | 1rSnXMr63jdCuegJFuidJqWxUPV7AtUf7  | 16777215                                         | 036ea839d22847ee1dce3bfc5b11f6cf785b0682db58c35b63d1342eb221c3490c | 2015-01-15
25  | 0000000000000000000000000000000000000000000000000000000001FA5EE5 | 15JhYXn6Mx3oF4Y7PcTAv2wVVAuCFFQNiP | 33554431                                         | 03057fbea3a2623382628dde556b2a0698e32428d3cd225f3bd034dca82dd7455a | 2015-01-15
26  | 000000000000000000000000000000000000000000000000000000000340326E | 1JVnST957hGztonaWK6FougdtjxzHzRMMg | 67108863                                         | 024e4f50a2a3eccdb368988ae37cd4b611697b26b29696e42e06d71368b4f3840f | 2015-01-15
27  | 0000000000000000000000000000000000000000000000000000000006AC3875 | 128z5d7nN7PkCuX5qoA4Ys6pmxUYnEy86k | 134217727                                        | 031a864bae3922f351f1b57cfdd827c25b7e093cb9c88a72c1cd893d9f90f44ece | 2015-01-15
28  | 000000000000000000000000000000000000000000000000000000000D916CE8 | 12jbtzBb54r97TCwW3G1gCFoumpckRAPdY | 268435455                                        | 03e9e661838a96a65331637e2a3e948dc0756e5009e7cb5c36664d9b72dd18c0a7 | 2015-01-16
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135 |                                                                  | 16RGFo6hjq9ym6Pj7N5H7L1NR1rVPJyw2v | 43556142965880123323311949751266331066367        | 02145d2611c823a396ef6712ce0f712f09b9b4f3135e3e0aa3230fb9b6d08d1e16 | ____-__-__
136 |                                                                  | 1UDHPdovvR985NrWSkdWQDEQ1xuRiTALq  | 87112285931760246646623899502532662132735        | ========================== U N K N O W N ========================= | ____-__-__
137 |                                                                  | 15nf31J46iLuK1ZkTnqHo7WgN5cARFK3RA | 174224571863520493293247799005065324265471       | ========================== U N K N O W N ========================= | ____-__-__
138 |                                                                  | 1Ab4vzG6wEQBDNQM1B2bvUz4fqXXdFk2WT | 348449143727040986586495598010130648530943       | ========================== U N K N O W N ========================= | ____-__-__
139 |                                                                  | 1Fz63c775VV9fNyj25d9Xfw3YHE6sKCxbt | 696898287454081973172991196020261297061887       | ========================== U N K N O W N ========================= | ____-__-__
140 |                                                                  | 1QKBaU6WAeycb3DbKbLBkX7vJiaS8r42Xo | 1393796574908163946345982392040522594123775      | 031f6a332d3c5c4f2de2378c012f429cd109ba07d69690c6c701b6bb87860d6640 | ____-__-__
141 |                                                                  | 1CD91Vm97mLQvXhrnoMChhJx4TP9MaQkJo | 2787593149816327892691964784081045188247551      | ========================== U N K N O W N ========================= | ____-__-__
142 |                                                                  | 15MnK2jXPqTMURX4xC3h4mAZxyCcaWWEDD | 5575186299632655785383929568162090376495103      | ========================== U N K N O W N ========================= | ____-__-__
143 |                                                                  | 13N66gCzWWHEZBxhVxG18P8wyjEWF9Yoi1 | 11150372599265311570767859136324180752990207     | ========================== U N K N O W N ========================= | ____-__-__
144 |                                                                  | 1NevxKDYuDcCh1ZMMi6ftmWwGrZKC6j7Ux | 22300745198530623141535718272648361505980415     | ========================== U N K N O W N ========================= | ____-__-__
145 |                                                                  | 19GpszRNUej5yYqxXoLnbZWKew3KdVLkXg | 44601490397061246283071436545296723011960831     | 03afdda497369e219a2c1c369954a930e4d3740968e5e4352475bcffce3140dae5 | ____-__-__
146 |                                                                  | 1M7ipcdYHey2Y5RZM34MBbpugghmjaV89P | 89202980794122492566142873090593446023921663     | ========================== U N K N O W N ========================= | ____-__-__
147 |                                                                  | 18aNhurEAJsw6BAgtANpexk5ob1aGTwSeL | 178405961588244985132285746181186892047843327    | ========================== U N K N O W N ========================= | ____-__-__
148 |                                                                  | 1FwZXt6EpRT7Fkndzv6K4b4DFoT4trbMrV | 356811923176489970264571492362373784095686655    | ========================== U N K N O W N ========================= | ____-__-__
149 |                                                                  | 1CXvTzR6qv8wJ7eprzUKeWxyGcHwDYP1i2 | 713623846352979940529142984724747568191373311    | ========================== U N K N O W N ========================= | ____-__-__
150 |                                                                  | 1MUJSJYtGPVGkBCTqGspnxyHahpt5Te8jy | 1427247692705959881058285969449495136382746623   | 03137807790ea7dc6e97901c2bc87411f45ed74a5629315c4e4b03a0a102250c49 | ____-__-__
151 |                                                                  | 13Q84TNNvgcL3HJiqQPvyBb9m4hxjS3jkV | 2854495385411919762116571938898990272765493247   | ========================== U N K N O W N ========================= | ____-__-__
152 |                                                                  | 1LuUHyrQr8PKSvbcY1v1PiuGuqFjWpDumN | 5708990770823839524233143877797980545530986495   | ========================== U N K N O W N ========================= | ____-__-__
153 |                                                                  | 18192XpzzdDi2K11QVHR7td2HcPS6Qs5vg | 11417981541647679048466287755595961091061972991  | ========================== U N K N O W N ========================= | ____-__-__
154 |                                                                  | 1NgVmsCCJaKLzGyKLFJfVequnFW9ZvnMLN | 22835963083295358096932575511191922182123945983  | ========================== U N K N O W N ========================= | ____-__-__
155 |                                                                  | 1AoeP37TmHdFh8uN72fu9AqgtLrUwcv2wJ | 45671926166590716193865151022383844364247891967  | 035cd1854cae45391ca4ec428cc7e6c7d9984424b954209a8eea197b9e364c05f6 | ____-__-__
156 |                                                                  | 1FTpAbQa4h8trvhQXjXnmNhqdiGBd1oraE | 91343852333181432387730302044767688728495783935  | ========================== U N K N O W N ========================= | ____-__-__
157 |                                                                  | 14JHoRAdmJg3XR4RjMDh6Wed6ft6hzbQe9 | 182687704666362864775460604089535377456991567871 | ========================== U N K N O W N ========================= | ____-__-__
158 |                                                                  | 19z6waranEf8CcP8FqNgdwUe1QRxvUNKBG | 365375409332725729550921208179070754913983135743 | ========================== U N K N O W N ========================= | ____-__-__
159 |                                                                  | 14u4nA5sugaswb6SZgn5av2vuChdMnD9E5 | 730750818665451459101842416358141509827966271487 | ========================== U N K N O W N ========================= | ____-__-__
160 |                                                                  | 1NBC8uXJy1GiJ6drkiZa1WuKn51ps7EPTv | 1461501637330902918203684832716283019655932542975| 02e0a8b039282faf6fe0fd769cfbc4b6b4cf8758ba68220eac420e32b91ddfa673 | ____-__-__

If you want - you can send me a donation to my BTC wallet address 31hgbukdkehcuxcedchkdbsrygegyefbvd
zielar (OP)
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January 19, 2020, 07:13:46 PM
Last edit: May 10, 2022, 09:42:53 AM by zielar
 #3


VanitySearch performance list

GPU:
GeForce RTX 2080 Ti: ~2564 Mkeys/s
GeForce RTX 2080 SUPER: ~2001 Mkeys/s**
Tesla V100-SXM2-16GB: ~1815 Mkeys/s
Tesla A10: ~1400 Mkeys/s**
GeForce RTX 2080 EVGA XC ULTRA: ~1425 Mkeys/s
GeForce RTX 2070: ~1470 Mkeys/s
GeForce RTX 2060 SUPER: ~1361 Mkeys/s**
GeForce GTX 1660 Ti: ~960 Mkeys/s
GeForce GTX 1080 Ti: ~900 Mkeys/s
GeForce GTX 1660: ~839 Mkeys/s
GeForce GTX 1080: ~672 Mkeys/s
GeForce GTX 1650: ~511 Mkeys/s
GeForce GTX 980: ~375 Mkeys/s
GeForce GTX 970: ~330 Mkeys/s
GeForce GTX 1060 3GB: ~321 Mkeys/s
GeForce GTX 1050 Ti: ~220 Mkeys/s
Tesla M60: ~185 Mkeys/s
GeForce GTX 960M: ~117 Mkeys/s
GeForce GTX 750: ~95 Mkeys/s
GeForce GT 520M: ~7 Mkeys/s

Compilation types of VanitySearch:
default is 128Mb threads for GPU
** - 256Mb threads for GPU
*** - 512Mb threads for GPU
Generally, it is confirmed that each higher thread compilation is more efficient and significantly increases the performance, but it is also worth noting that the latest cards (starting from RTX) do not work on the 512Mb version due to the changed architecture. For these, the 256Mb version is recommended

CPU:
i7-7700K CPU: ~22 Mkeys/s | using 8 threads [-t 8]

Many thanks to DaveF who has collected the vast majority of the data here.
It was thanks to him that I decided to put this data here and express my willingness to supplement it with more items.

If you have equipment that is not listed above - I will be grateful for info on its performance in VanitySearch (version with integrated BitCrack options).
If you have the equipment listed above and you managed to get better performance - also let us know how you did it (additional start command, gridsize etc.) for the update.

Latest VanitySearch builds with BitCrack features working on all NVIDIA cards

Compilations made with the use of CUDA version 11.6, so for the program to work it is necessary to update the drivers in the system to the latest ones that are available. I have compiled for each GPU architecture separately - as listed below

LINUX

After downloading, execute the command chmod +x vanitysearch in linux
The downloaded file is ready, for example, to start working with the ttd client needed to start participating in pool #64.
Just download the selected compilation to the same folder as the ttdclient and the settings.ini file

For the lazy, I also provide ttdclient to work with the above in linux: http://zielar.pl/ttdclient [run the chmod +x ttdclient command after the download], and sample settings.ini: http://zielar.pl/settings.ini

MS Windows:
comming soon


NVIDIA Kepler GPUs: GeForce 700, GT-730, Tesla K40 [SM_35]; Tesla K80 [SM_37]
NVIDIA Maxwell GPUs: Tesla/Quadro M series [SM_50]; Quadro M6000 , GeForce 900, GTX-970, GTX-980, GTX Titan X [SM_52]; Tegra (Jetson) TX1 / Tegra X1, Drive CX, Drive PX, Jetson Nano [SM_53]
NVIDIA Pascal GPUs: Quadro GP100, Tesla P100, DGX-1 (Generic Pascal) [SM_60]; GTX 1080, GTX 1070, GTX 1060, GTX 1050, GTX 1030 (GP108), GT 1010 (GP108) Titan Xp, Tesla P40, Tesla P4, Discrete GPU on the NVIDIA Drive PX2 [SM_61]; Integrated GPU on the NVIDIA Drive PX2, Tegra (Jetson) TX2 [SM_62]
NVIDIA Volta GPUs: DGX-1 with Volta, Tesla V100, GTX 1180 (GV104), Titan V, Quadro GV100 [SM_70]
NVIDIA Xavier GPUs: Jetson AGX Xavier, Drive AGX Pegasus, Xavier NX [SM_72]
NVIDIA Turing GPUs: GTX/RTX Turing – GTX 1660 Ti, RTX 2060, 2070, 2080, Titan RTX, Quadro RTX 4000, 5000, 6000, 8000, Quadro T1000/T2000, Tesla T4 [SM_75]
NVIDIA Ampere GPUs: NVIDIA A100, NVIDIA DGX-A100 [SM_80]; Tesla GA10x cards, RTX 3050, 3060, 3070, 3080, 3090, RTX A2000, A3000, A4000, A5000, A6000, NVIDIA A40, A10, A16, A40, A2 Tensor Core GPU [SM_86]

If you want - you can send me a donation to my BTC wallet address 31hgbukdkehcuxcedchkdbsrygegyefbvd
zielar (OP)
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January 19, 2020, 07:14:22 PM
Last edit: May 10, 2022, 09:43:19 AM by zielar
 #4

...reserved for OP update

If you want - you can send me a donation to my BTC wallet address 31hgbukdkehcuxcedchkdbsrygegyefbvd
sssergy2705
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January 19, 2020, 10:08:48 PM
 #5

This is all well and good, but leave the old discussion links. There are interesting posts there.
sssergy2705
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January 19, 2020, 10:14:27 PM
 #6

And of course I would like to know about the scanned ranges. You know that not everyone has high-performance equipment, but everyone wants to participate.
For example, I use a python script.
zielar (OP)
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January 19, 2020, 11:43:31 PM
 #7

Due to the nature of the issue of scanned ranges and the inability to confirm the reliability of such data - listing scanned ranges is not a good idea. There is, however, a group that jointly finds the key to the current level, where using the database - automatically checked ranges are excluded.

I am asking for suggestions to expand the topic with interesting data ... What would you like to see in the main thread? I will soon introduce a profitability table relative to GPU cards in proportion to price and performance along with the recommended setting for BitCrack.

If you want - you can send me a donation to my BTC wallet address 31hgbukdkehcuxcedchkdbsrygegyefbvd
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January 20, 2020, 01:27:09 AM
 #8

-snip-
... What would you like to see in the main thread?
-snip-

I guess that posting the scanned ranges here is not a good idea. Probably create separate topic for that if interesting. But practiclly it makes no sense.

Better to post some ECDSA investigations, new scripts, new ideas, ECDSA properties, etc. Something which could improve the search speed or approach.

almightyruler
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January 20, 2020, 04:15:11 AM
 #9

Hi to the new thread. Posting scanned ranges might encourage trolling - people posting that they have scanned a range when they haven't - but given the search space is so big, the effect of such a lie is probably going to be virtually nil?
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January 22, 2020, 11:12:52 PM
 #10

While not part of the puzzle, but having a bit to do with why it was created in the first place.. an interesting exercise  no reward other than knowledge though I'll probably put a pi with a randomizied python script on it. finding a collision for the first two in the puzzle and see how far apart they are, might give a "clearer view" of the curve if that makes any sense. - Though that would probably end up being harder than finding #160 - Still, worth thinking about.
n00by
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February 05, 2020, 06:34:56 PM
 #11

I have a search algorithm that is several times faster than the @57fe https://bitcointalk.org/index.php?topic=5166284.msg52582231#msg52582231 algorithm in single-threaded mode. According to my calculations, in skilled hands, you can keep within a month on a good server in the cloud to calculate 110 tasks. Server costs will reduce the reward by about half. This is more interesting than simple mining.
The algorithm can only be shifted to FPGA. Modular arithmetic does not imply the use of ASIC.

If there are interested people, I can post the evidence in the video.

Python does not assume that code is closed when used by other people, so I can not publish the source code, and the prototype algorithm is implemented in python.

Sorry for my English, but I'm not a native speaker of this language
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February 05, 2020, 06:56:15 PM
 #12

I have a search algorithm that is several times faster than the @57fe https://bitcointalk.org/index.php?topic=5166284.msg52582231#msg52582231 algorithm in single-threaded mode. According to my calculations, in skilled hands, you can keep within a month on a good server in the cloud to calculate 110 tasks. Server costs will reduce the reward by about half. This is more interesting than simple mining.
The algorithm can only be shifted to FPGA. Modular arithmetic does not imply the use of ASIC.

If there are interested people, I can post the evidence in the video.

Python does not assume that code is closed when used by other people, so I can not publish the source code, and the prototype algorithm is implemented in python.

Sorry for my English, but I'm not a native speaker of this language
your link not in post at 57fe.
which from your algorimt is faster?
n00by
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February 05, 2020, 07:21:36 PM
Last edit: February 05, 2020, 08:06:44 PM by n00by
 #13

your link not in post at 57fe.
which from your algorimt is faster?

My link to the latest post from 57fe. My algorithm is based on a different math. And he is faster
PS4ever220
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February 05, 2020, 08:28:17 PM
 #14

your link not in post at 57fe.
which from your algorimt is faster?

My link to the latest post from 57fe. My algorithm is based on a different math. And he is faster

which python libraries you using if its no secret ?
And i'm interested in your video as well, please show if you not mind.
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February 06, 2020, 12:05:41 AM
 #15

-snip-
If there are interested people, I can post the evidence in the video.

Post the evidence please

n00by
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February 06, 2020, 07:48:41 AM
 #16

which python libraries you using if its no secret ?
And i'm interested in your video as well, please show if you not mind.

https://drive.google.com/open?id=1abZRyPMhC0A5W7esdp-odh_-ToB6hHaw
iparktur
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February 06, 2020, 08:42:40 AM
 #17

which python libraries you using if its no secret ?
And i'm interested in your video as well, please show if you not mind.

https://drive.google.com/open?id=1abZRyPMhC0A5W7esdp-odh_-ToB6hHaw

Can you send this python file to me in PM for testing?
supika
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February 06, 2020, 10:02:43 AM
 #18

which python libraries you using if its no secret ?
And i'm interested in your video as well, please show if you not mind.

https://drive.google.com/open?id=1abZRyPMhC0A5W7esdp-odh_-ToB6hHaw

Can you send this python file to me in PM for testing?

Sharing is caring Wink
n00by
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February 06, 2020, 10:36:42 AM
 #19

Can you send this python file to me in PM for testing?

I am now modifying the code for execution in multiple threads. After that I’ll try to run 110 bit in a cloud server to find a solution.
I don’t think you would show anyone such code
bulleteyedk
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February 06, 2020, 10:45:05 AM
 #20

please let us know more...

that video running a python script is dated in october 2019, so have you made any improvements since then?
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