I currently use a Radeon 5770 (please don't judge, electricity is not a big issue and we're in a bear market right now, so it's mostly experimentation for now) and Claymore CryptoNote GPU Miner v9.7.
GPU is overclocked to 960/1320 MHz (core/memory) and yields 176-177 H/s (stock 850/1200 clocks yield 165-166 H/s). According to HWiNFO64, GPU utilization is 99-100% and VRAM usage is ~800MB. This old and unsupported miner software is utilizing my old GPU to its full potential.
The thing is, I'm trying to prepare for the inevitable Monero v7 algo change (most altcoins will also adopt it) and I'm experimenting with different miner apps (xmrig-amd, xmr-stak).
Both xmrig-amd and xmr-stak (latest versions) only give me ~65 H/s, which is pretty low, even lower than my CPU*.
Default hash count is 160 threads and if I try it to increase it to 320, then I get OpenCL errors that the memory capacity does not suffice. GPU utilization is 50% and VRAM usage is ~500MB. Something is clearly not optimal...
On top of that, these miners slow down my PC a lot, while Claymore v9.7 doesn't...
* My CPU (Q9550 overclocked to 422 FSB, 3587 MHz) yields 112-113 H/s with xmrig.
I'll post my configs with some comments in case someone can help:
-o ssl://server:3333
-allpools 1
-u wallet_address
-p w=desktop_PC_GPU
-a 3 #optimized mining algo for TeraScale/VLIW GPUs
-dbg -1
-li 1 #low intensity to be able to use my PC
-nofee 1 #I disabled the fee because it uses old pools that lose connection pretty often and thus mining stops altogether
-h 320 #320 threads 2MB each = 640MB VRAM needed
{
"algo": "cryptonight",
"background": false,
"colors": true,
"donate-level": 1,
"log-file": null,
"print-time": 60,
"retries": 5,
"retry-pause": 5,
"opencl-platform": 0,
"threads": [
{
"index": 0,
"intensity": 160,
"worksize": 8,
"affine_to_cpu": false
}
],
"pools": [
{
"url": "server:3333",
"user": "wallet_address",
"pass": "w=desktop_PC_GPU",
"keepalive": true,
"nicehash": false,
"variant": -1
}
],
"api": {
"port": 0,
"access-token": null,
"worker-id": null
}
}/*
* GPU configuration. You should play around with intensity and worksize as the fastest settings will vary.
* index - GPU index number usually starts from 0
* intensity - Number of parallel GPU threads (nothing to do with CPU threads)
* worksize - Number of local GPU threads (nothing to do with CPU threads)
* affine_to_cpu - This will affine the thread to a CPU. This can make a GPU miner play along nicer with a CPU miner.
* strided_index - switch memory pattern used for the scratch pad memory
* 2 = chunked memory, chunk size is controlled by 'mem_chunk'
* required: intensity must be a multiple of worksize
* 1 or true = use 16byte contiguous memory per thread, the next memory block has offset of intensity blocks
* 0 or false = use a contiguous block of memory per thread
* mem_chunk - range 0 to 18: set the number of elements (16byte) per chunk
* this value is only used if 'strided_index' == 2
* element count is computed with the equation: 2 to the power of 'mem_chunk' e.g. 4 means a chunk of 16 elements(256byte)
* comp_mode - Compatibility enable/disable the automatic guard around compute kernel which allows
* to use a intensity which is not the multiple of the worksize.
* If you set false and the intensity is not multiple of the worksize the miner can crash:
* in this case set the intensity to a multiple of the worksize or activate comp_mode.
* "gpu_threads_conf" :
* [
* { "index" : 0, "intensity" : 1000, "worksize" : 8, "affine_to_cpu" : false, "strided_index" : true, "mem_chunk" : 2, "comp_mode" : true },
* ],
* If you do not wish to mine with your AMD GPU(s) then use:
* "gpu_threads_conf" :
* null,
*/
"gpu_threads_conf" : [
// gpu: Juniper memory:384
// compute units: 10
{ "index" : 0,
"intensity" : 160, "worksize" : 8,
"affine_to_cpu" : false, "strided_index" : 1, "mem_chunk" : 2,
"comp_mode" : true
},
],
/*
* Platform index. This will be 0 unless you have different OpenCL platform - eg. AMD and Intel.
*/
"platform_index" : 0,
Is there any hope for TeraScale/VLIW GPUs (Radeon 5xxx/6xxx) after the Monero v7 fork?
