glph3k / cast_xmr Goto Github PK

The algorithm is basically variation of CryptoNight Turtle, but with extra bit in AES mask...

Technically speaking CryptoNight Turtle is CryptoNight Ultra Lite Variant 2
Technically speaking CryptoNight Talleo is CryptoNight Ultra Variant 2

The algorithms were written originally by same person and released both on multihashing repository used by TurtleCoin.

Hi,

is it possible to get a linux version of the same ? I dont have windows licenses to be able to run it. and I dont want to buy any either. thnx

You can find more details here:
https://github.com/artocash/arto-miner/tree/master/xmrstak
Thanks @glph3k

Hello,
Could you please implement the new MSR algorithm: Cryptonight-Fast
Here details:
masari-project/masari@28790b7
Thanks

Gandalph.

Would you consider adding a header to the JSON api that responds with'*' for the Access-Control-Allow-Origin header?

e.g. "Access-Control-Allow-Origin":"*" or something to that effect in your code.

This would make the utility of the json report far better.

When using Cast XMR Vega 1.7.1 just the first card (0) is detected and mining ok.
The second one is not detected.
I have tried -g 0,1 etc
Tried without -g
Not working

[12:04:45] Initializing GPU, loading kernel ...
Detected OpenCL Platform: OpenCL 2.0 AMD-APP (2442.12)
Blockchain Compute Driver detected.
GPU0: Radeon RX 580 Series (Ellesmere) | 36 Compute Units | Memory (MB): 8192 | Intensity: 7 / 10
[12:04:46] Connecting to bittube.miner.rocks:7777 ...
[12:04:46] Connected to pool.

The one is not working(detected) is a vega 64 card
cast_xmr-vega --algo=-5 -S bittube.miner.rocks:7777 -u xxx -g 0,1
Any ideas?

Hi there,

We are switching to a modified CryptoNight Heavy algo (CryptoNight Haven) in our next hardfork due next week. It would be great to have a compiled Cast XMR ready for the release as we have a huge amount of miners that use Cast.

The tweak is very small you can find the details here:
havenprotocol/haven@be8648c

This was my PR to xmr-stak with the changes:
https://github.com/fireice-uk/xmr-stak/pull/1639/files

Thank you!

Hi glph3k, Could you contact the team of Sumokoin for their upcoming update? SUMO will have algorithm changing issue but it's not same as Monero's V7, and that require mining software to be updated too.

Otherwise, RX Vega might not able to mine SUMO after the update in April.

Thanks

On website Ubuntu download page, it says:
Updated on January 26th, 2018 to version 1.7.1

instead of:
Updated on January 26th, 2019 to version 1.7.1

Page url: http://www.gandalph3000.com/cast_xmr/linux/linux_version_of_cast-xmr-cryptonight-monero-miner-for-rx-vega-gpus/

It makes the software look a bit older than it is... :)

[17:09:54] Connecting to xlc.crypto-coins.club:6666 ...
[17:09:54] Connected to pool.
[17:09:55] SOCKET ERROR - invalid address used for login
[17:09:55] SOCKET ERROR - RECEIVE error: A blocking operation was interrupted by a call to WSACancelBlockingCall.
[17:09:55] Connecting to Pool failed. Retrying in 20 secs ...

I have tried everything.
I get this msg all the time and not be able to connect to any pool.
Below is my command line.

cast_xmr-vega.exe --forcecompute --fastjobswitch --nonicehash --algo 1 --gpu 0,1,2,3,4,5,6,7,8,9,10,11 -S xlc.crypto-coins.club:6666 -u LsDjN4vDhDSjT21daqyiZ96z6vaZeyssGLcVUAfjYUxjdwuAZ9ki6iNZYNupRwKvmGdnoV1GAwmoHGgquP2eNdyC3v4hRPo.f09f74cd004c7d91eb020bfee15c64c7820fd48fdbb978f95697acae15240ce2 -p x pause

Im running 18.3.4 and RX580's x 13 units.
Help.

Hello @glph3k

When I want to run your miner on my machine, I get the following error:

[13:39:44] Initializing GPU, loading kernel ...
Detected OpenCL Platform: OpenCL 2.1 AMD-APP (2679.0)
Driver Version OK.
Fast job switching mode enabled.
GPU0: gfx900 (card-1) | 56 Compute Units | Memory (MB): 8176 | Intensity: 7 / 10
[13:39:44] Error clBuildProgramm -11

It's a dedicated server with two Xeon E5-2680, running Ubuntu 18.04 (Kernel 4.15.0-45-generic).
I had two R9 390s running fine with exactly this setup before,
but since I replaced them with an RX Vega 56 my OpenCL setup seems to be broken.

Do you have an idea, where this could come from?
Or some debugging tool I can test my OpenCL setup with?

That would be great.

FYI:
Clinfo recognizes the card correctly:

Number of platforms:				 1
  Platform Profile:				 FULL_PROFILE
  Platform Version:				 OpenCL 2.1 AMD-APP (2783.0)
  Platform Name:				 AMD Accelerated Parallel Processing
  Platform Vendor:				 Advanced Micro Devices, Inc.
  Platform Extensions:				 cl_khr_icd cl_amd_event_callback cl_amd_offline_devices 


  Platform Name:				 AMD Accelerated Parallel Processing
Number of devices:				 1
  Device Type:					 CL_DEVICE_TYPE_GPU
  Vendor ID:					 1002h
  Board name:					 Vega [Radeon RX Vega]
  Device Topology:				 PCI[ B#131, D#0, F#0 ]
  Max compute units:				 56
  Max work items dimensions:			 3
    Max work items[0]:				 1024
    Max work items[1]:				 1024
    Max work items[2]:				 1024
  Max work group size:				 256
  Preferred vector width char:			 4
  Preferred vector width short:			 2
  Preferred vector width int:			 1
  Preferred vector width long:			 1
  Preferred vector width float:			 1
  Preferred vector width double:		 1
  Native vector width char:			 4
  Native vector width short:			 2
  Native vector width int:			 1
  Native vector width long:			 1
  Native vector width float:			 1
  Native vector width double:			 1
  Max clock frequency:				 1590Mhz
  Address bits:					 64
  Max memory allocation:			 7287183769
  Image support:				 Yes
  Max number of images read arguments:		 128
  Max number of images write arguments:		 8
  Max image 2D width:				 16384
  Max image 2D height:				 16384
  Max image 3D width:				 2048
  Max image 3D height:				 2048
  Max image 3D depth:				 2048
  Max samplers within kernel:			 26751
  Max size of kernel argument:			 1024
  Alignment (bits) of base address:		 1024
  Minimum alignment (bytes) for any datatype:	 128
  Single precision floating point capability
    Denorms:					 Yes
    Quiet NaNs:					 Yes
    Round to nearest even:			 Yes
    Round to zero:				 Yes
    Round to +ve and infinity:			 Yes
    IEEE754-2008 fused multiply-add:		 Yes
  Cache type:					 Read/Write
  Cache line size:				 64
  Cache size:					 16384
  Global memory size:				 8573157376
  Constant buffer size:				 7287183769
  Max number of constant args:			 8
  Local memory type:				 Scratchpad
  Local memory size:				 65536
  Max pipe arguments:				 16
  Max pipe active reservations:			 16
  Max pipe packet size:				 2992216473
  Max global variable size:			 7287183769
  Max global variable preferred total size:	 8573157376
  Max read/write image args:			 64
  Max on device events:				 1024
  Queue on device max size:			 8388608
  Max on device queues:				 1
  Queue on device preferred size:		 262144
  SVM capabilities:				 
    Coarse grain buffer:			 Yes
    Fine grain buffer:				 Yes
    Fine grain system:				 No
    Atomics:					 No
  Preferred platform atomic alignment:		 0
  Preferred global atomic alignment:		 0
  Preferred local atomic alignment:		 0
  Kernel Preferred work group size multiple:	 64
  Error correction support:			 0
  Unified memory for Host and Device:		 0
  Profiling timer resolution:			 1
  Device endianess:				 Little
  Available:					 Yes
  Compiler available:				 Yes
  Execution capabilities:				 
    Execute OpenCL kernels:			 Yes
    Execute native function:			 No
  Queue on Host properties:				 
    Out-of-Order:				 No
    Profiling :					 Yes
  Queue on Device properties:				 
    Out-of-Order:				 Yes
    Profiling :					 Yes
  Platform ID:					 0x7f57887f19d0
  Name:						 gfx900
  Vendor:					 Advanced Micro Devices, Inc.
  Device OpenCL C version:			 OpenCL C 2.0 
  Driver version:				 2783.0 (HSA1.1,LC)
  Profile:					 FULL_PROFILE
  Version:					 OpenCL 1.2 
  Extensions:					 cl_khr_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_gl_sharing cl_amd_device_attribute_query cl_amd_media_ops cl_amd_media_ops2 cl_khr_subgroups cl_khr_depth_images cl_amd_copy_buffer_p2p cl_amd_assembly_program

Tax-Project uses the CryptoNight (AscendingNight) hash algorithm, which is optimized for CPU-based mining and GPU resistance, with the Algo specializing in fair sharing of the hashrate.
Tax forked from CN-Heavy to to their own custom variant recently and was hoping you could add support for it.

AscendingNight is similar to CryptoNight (same scratchpad implode and explode) but it utilizes a different main algorithm. While CryptoNight uses one aes step every second step, AscendingNight uses one AES every fourth step, has some substitutional parts and things like that to perform less calculations for more memory intesety.
In our private testing we came across performance boosts of 10% to 30% on Ryzen CPUs and up to 100% on older i7s.
Since the memory utilisation is still the same, the algorithm is just as fast on GPU (mathematically speaking, not tested yet).

The thing with Heavy, light and fast is just that, similar to CryptoNight, you can apply all the causal variations like CN-Heavy on AN as well (since it's just changing memory and iteration variables).

The point with the reference implementation of AscendingNight is that, while it's modular, it's still using 2MB as a scratchpad size and 2^14 iterations to increase the speeds of the validation process.
By increasing the iteration number to the casual CryptoNight step count of 2^20 you'd see an even higher boost in the performance of CPUs compared to GPUs.

The important changes were done in the post_aes macro. It can be found in here:
https://github.com/Tax-Project/Tax/blob/master/src/crypto/slow-hash.c#L264

Links
├──.Reference implementation
│.......├──..https://github.com/Tax-Project/Tax/blob/master/src/crypto/slow-hash.c
│.......├──..http://clashproject.org/tax/
│.......├──..https://github.com/Tax-Project
│.......├──..https://github.com/Tax-Project/Miner-UI
├──.Test-Pool
│.......├──..http://207.180.246.163/#
├──.Wallet
└──────.http://clashproject.org/tax/

Let me know if you need any help or further information.