The cuda31 app sucks. My GPUs can run on the OpenCL app much, much faster. At a rate of over 2:1. I can complete ~40 cuda31 tasks per hour while the same system can complete ~90 opencl tasks in a single hour.

Yet, the server keeps sending me cuda31 tasks. I have no way to stop it other than aborting those tasks until I get a bunch of opencl tasks.

This has been requested many times, unfortunately not implemented yet. What you can do yourself is using the Anonymous platform mechanism to force the OpenCL app. This should not cause any issues, since the applications don't change here frequently.

I posted a working app_info.xml in this message, it's for the ATI CAL app, but you can use it as reference, the correct files and their names and other information for your Nvidia OpenCl app you can find in your client_state.xml once you processed an OpenCL task (you don't need to download or modify any files, you should have them, skip those steps).

---

Appears to be for Windows, not sure it would work in Linux.

I did look that over and looked over the files in the Linux install, but I can't seem to figure out what file names to use for Linux that corresponds with the Windows file name.

All the information is in your client_state.xml actually, the app_info.xml isn't much different, I wrote one even for Android.

For my GTX 275 and the cuda app (and the CPU app) the relevant part is:

<app>
    <name>dnetc</name>
    <user_friendly_name>Distributed.net Client</user_friendly_name>
    <non_cpu_intensive>0</non_cpu_intensive>
</app>
<file>
    <name>dnetc_wrapper_1.3_windows_intelx86__cuda31.exe</name>
    <nbytes>418304.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <executable/>
    <signature_required/>
    <file_signature>
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9778ca62866afb452770a91f24faab7b0c6dc9041232604f9ad73df3a234702a

.
</file_signature>
    <download_url>http://moowrap.net/download/dnetc_wrapper_1.3_windows_intelx86__cuda31.exe</download_url>
</file>
<file>
    <name>dnetc518-win32-x86-cuda31.exe</name>
    <nbytes>218624.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <executable/>
    <signature_required/>
    <file_signature>
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b9c801449e6a45e38f9a4dfaeeacdb72b1fb2f61458772d2d346f2f315a1c1cc
.
</file_signature>
    <download_url>http://moowrap.net/download/dnetc518-win32-x86-cuda31.exe</download_url>
</file>
<file>
    <name>dnetc-gpu-1.3.ini</name>
    <nbytes>447.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <signature_required/>
    <file_signature>
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e3f6de14905430e645ce714876476749952aefa7747f47751ddf8f4b8f6cc121

.
</file_signature>
    <download_url>http://moowrap.net/download/dnetc-gpu-1.3.ini</download_url>
</file>
<file>
    <name>job-cuda31-1.00.xml</name>
    <nbytes>229.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <signature_required/>
    <file_signature>
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.
</file_signature>
    <download_url>http://moowrap.net/download/job-cuda31-1.00.xml</download_url>
</file>
<file>
    <name>cudart32_31_9.dll</name>
    <nbytes>250472.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <signature_required/>
    <file_signature>
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1e1dbfab0711adae54bc4a1953316f4603faaf3916d1dd99293367b053e44918

.
</file_signature>
    <download_url>http://moowrap.net/download/cudart32_31_9.dll</download_url>
</file>
<file>
    <name>dnetc_wrapper_1.5_windows_x86_64.exe</name>
    <nbytes>1241600.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <executable/>
    <signature_required/>
    <file_signature>
17be8a6658802c0dc31215a2b142c1d1257a6d892a5e1b62487a4aab995c96d8

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.
</file_signature>
    <download_url>http://moowrap.net/download/dnetc_wrapper_1.5_windows_x86_64.exe</download_url>
</file>
<file>
    <name>dnetc521-win64-amd64.exe</name>
    <nbytes>1554432.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <executable/>
    <signature_required/>
    <file_signature>
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.
</file_signature>
    <download_url>http://moowrap.net/download/dnetc521-win64-amd64.exe</download_url>
</file>
<file>
    <name>dnetc-cpu-1.4.ini</name>
    <nbytes>524.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <signature_required/>
    <file_signature>
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.
</file_signature>
    <download_url>http://moowrap.net/download/dnetc-cpu-1.4.ini</download_url>
</file>
<file>
    <name>job-win64-521.1.xml</name>
    <nbytes>250.000000</nbytes>
    <max_nbytes>0.000000</max_nbytes>
    <status>1</status>
    <signature_required/>
    <file_signature>
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.
</file_signature>
    <download_url>http://moowrap.net/download/job-win64-521.1.xml</download_url>
</file>
<app_version>
    <app_name>dnetc</app_name>
    <version_num>103</version_num>
    <platform>windows_intelx86</platform>
    <avg_ncpus>1.000000</avg_ncpus>
    <flops>71085192687.983200</flops>
    <plan_class>cuda31</plan_class>
    <api_version>6.13.12</api_version>
    <file_ref>
        <file_name>dnetc_wrapper_1.3_windows_intelx86__cuda31.exe</file_name>
        <main_program/>
    </file_ref>
    <file_ref>
        <file_name>dnetc518-win32-x86-cuda31.exe</file_name>
        <copy_file/>
    </file_ref>
    <file_ref>
        <file_name>dnetc-gpu-1.3.ini</file_name>
        <open_name>dnetc.ini</open_name>
        <copy_file/>
    </file_ref>
    <file_ref>
        <file_name>job-cuda31-1.00.xml</file_name>
        <open_name>job.xml</open_name>
        <copy_file/>
    </file_ref>
    <file_ref>
        <file_name>cudart32_31_9.dll</file_name>
        <copy_file/>
    </file_ref>
    <coproc>
        <type>NVIDIA</type>
        <count>1.000000</count>
    </coproc>
    <gpu_ram>33554432.000000</gpu_ram>
    <dont_throttle/>
</app_version>
<app_version>
    <app_name>dnetc</app_name>
    <version_num>105</version_num>
    <platform>windows_x86_64</platform>
    <avg_ncpus>1.000000</avg_ncpus>
    <flops>7498889328.256757</flops>
    <api_version>7.13.0</api_version>
    <file_ref>
        <file_name>dnetc_wrapper_1.5_windows_x86_64.exe</file_name>
        <main_program/>
    </file_ref>
    <file_ref>
        <file_name>dnetc521-win64-amd64.exe</file_name>
        <copy_file/>
    </file_ref>
    <file_ref>
        <file_name>dnetc-cpu-1.4.ini</file_name>
        <open_name>dnetc.ini</open_name>
        <copy_file/>
    </file_ref>
    <file_ref>
        <file_name>job-win64-521.1.xml</file_name>
        <open_name>job.xml</open_name>
        <copy_file/>
    </file_ref>
    <is_wrapper/>
</app_version>

If you post that part of your client_state.xml, I can write for you the app_info.xml file.

---

<client_state>
<host_info>
<timezone>-14400</timezone>
<domain_name>epyc-2</domain_name>
<ip_addr>127.0.1.1</ip_addr>
<host_cpid>a82e4930039b4da5db5c648bdeb2ce4e</host_cpid>
<p_ncpus>64</p_ncpus>
<p_vendor>AuthenticAMD</p_vendor>
<p_model>AMD Eng Sample: 100-000000054-05_32/24_Y [Family 23 Model 49 Stepping 0]</p_model>
<p_features>fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate sme ssbd mba sev ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip rdpid overflow_recov succor smca</p_features>
<p_fpops>1000000000.000000</p_fpops>
<p_iops>1000000000.000000</p_iops>
<p_membw>1000000000.000000</p_membw>
<p_calculated>1678569620.283414</p_calculated>
<p_vm_extensions_disabled>0</p_vm_extensions_disabled>
<m_nbytes>135043411968.000000</m_nbytes>
<m_cache>524288.000000</m_cache>
<m_swap>2147479552.000000</m_swap>
<d_total>982899539968.000000</d_total>
<d_free>914710327296.000000</d_free>
<os_name>Linux Linuxmint</os_name>
<os_version>Linux Mint 20.3 [5.4.0-91-generic|libc 2.31 (Ubuntu GLIBC 2.31-0ubuntu9.2)]</os_version>
<n_usable_coprocs>6</n_usable_coprocs>
<wsl_available>0</wsl_available>
<coprocs>
<coproc_cuda>
<count>6</count>
<name>NVIDIA GeForce RTX 3070</name>
<available_ram>4150263808.000000</available_ram>
<have_cuda>1</have_cuda>
<have_opencl>1</have_opencl>
<peak_flops>10775040000000.000000</peak_flops>
<cudaVersion>11070</cudaVersion>
<drvVersion>51586</drvVersion>
<totalGlobalMem>4294967295.000000</totalGlobalMem>
<sharedMemPerBlock>49152.000000</sharedMemPerBlock>
<regsPerBlock>65536</regsPerBlock>
<warpSize>32</warpSize>
<memPitch>2147483647.000000</memPitch>
<maxThreadsPerBlock>1024</maxThreadsPerBlock>
<maxThreadsDim>1024 1024 64</maxThreadsDim>
<maxGridSize>2147483647 65535 65535</maxGridSize>
<clockRate>1830000</clockRate>
<totalConstMem>65536.000000</totalConstMem>
<major>8</major>
<minor>6</minor>
<textureAlignment>512.000000</textureAlignment>
<deviceOverlap>1</deviceOverlap>
<multiProcessorCount>46</multiProcessorCount>
<coproc_opencl>
<name>NVIDIA GeForce RTX 3070</name>
<vendor>NVIDIA Corporation</vendor>
<vendor_id>4318</vendor_id>
<available>1</available>
<half_fp_config>0</half_fp_config>
<single_fp_config>191</single_fp_config>
<double_fp_config>63</double_fp_config>
<endian_little>1</endian_little>
<execution_capabilities>1</execution_capabilities>
<extensions>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_fp64 cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_device_uuid cl_khr_pci_bus_info cl_khr_external_semaphore cl_khr_external_memory cl_khr_external_semaphore_opaque_fd cl_khr_external_memory_opaque_fd</extensions>
<global_mem_size>8370061312</global_mem_size>
<local_mem_size>49152</local_mem_size>
<max_clock_frequency>1830</max_clock_frequency>
<max_compute_units>46</max_compute_units>
<nv_compute_capability_major>8</nv_compute_capability_major>
<nv_compute_capability_minor>6</nv_compute_capability_minor>
<amd_simd_per_compute_unit>0</amd_simd_per_compute_unit>
<amd_simd_width>0</amd_simd_width>
<amd_simd_instruction_width>0</amd_simd_instruction_width>
<opencl_platform_version>OpenCL 3.0 CUDA 11.7.102</opencl_platform_version>
<opencl_device_version>OpenCL 3.0 CUDA</opencl_device_version>
<opencl_driver_version>515.86.01</opencl_driver_version>
</coproc_opencl>
<pci_info>
<bus_id>1</bus_id>
<device_id>0</device_id>
<domain_id>0</domain_id>
</pci_info>
<pci_info>
<bus_id>65</bus_id>
<device_id>0</device_id>
<domain_id>0</domain_id>
</pci_info>
<pci_info>
<bus_id>129</bus_id>
<device_id>0</device_id>
<domain_id>0</domain_id>
</pci_info>
<pci_info>
<bus_id>130</bus_id>
<device_id>0</device_id>
<domain_id>0</domain_id>
</pci_info>
<pci_info>
<bus_id>193</bus_id>
<device_id>0</device_id>
<domain_id>0</domain_id>
</pci_info>
<pci_info>
<bus_id>194</bus_id>
<device_id>0</device_id>
<domain_id>0</domain_id>
</pci_info>
</coproc_cuda>
</coprocs>
</host_info>
<time_stats>
<on_frac>0.991558</on_frac>
<connected_frac>-1.000000</connected_frac>
<cpu_and_network_available_frac>1.000000</cpu_and_network_available_frac>
<active_frac>1.000000</active_frac>
<gpu_active_frac>0.999977</gpu_active_frac>
<client_start_time>1679796548.411848</client_start_time>
<total_start_time>1678569666.567551</total_start_time>
<total_duration>1270658.347323</total_duration>
<total_active_duration>1270658.347323</total_active_duration>
<total_gpu_active_duration>1270576.954426</total_gpu_active_duration>
<previous_uptime>52640.260177</previous_uptime>
<last_update>1679849178.569892</last_update>
</time_stats>
<net_stats>
<bwup>326685.985977</bwup>
<avg_up>265987763.004067</avg_up>
<avg_time_up>1679849187.948746</avg_time_up>
<bwdown>73864594.000365</bwdown>
<avg_down>109380130848.531219</avg_down>
<avg_time_down>1679848287.776949</avg_time_down>
</net_stats>
<project>
<master_url>https://sech.me/boinc/Amicable/</master_url>
<project_name>Amicable Numbers</project_name>
<symstore></symstore>
<user_name>Skillz</user_name>
<team_name>TeAm AnandTech</team_name>
<host_venue></host_venue>
<email_hash>7701f3a04f7e7d1e459351c1897c3ba3</email_hash>
<cross_project_id>b032fff82f26d5964a87ce2450e52a51</cross_project_id>
<external_cpid>cc2bdbcee7976d78486beeeb937bd376</external_cpid>
<cpid_time>1524743419.000000</cpid_time>
<user_total_credit>1012112135.230008</user_total_credit>
<user_expavg_credit>16546822.839927</user_expavg_credit>
<user_create_time>1524743419.000000</user_create_time>
<rpc_seqno>35947</rpc_seqno>
<userid>10035</userid>
<teamid>174</teamid>
<hostid>200770</hostid>
<host_total_credit>143847185.783213</host_total_credit>
<host_expavg_credit>8365948.668748</host_expavg_credit>
<host_create_time>1678570194.000000</host_create_time>
<nrpc_failures>0</nrpc_failures>
<master_fetch_failures>0</master_fetch_failures>
<min_rpc_time>0.000000</min_rpc_time>
<next_rpc_time>0.000000</next_rpc_time>
<rec>7264165.630973</rec>
<rec_time>1679849153.205769</rec_time>
<resource_share>100.000000</resource_share>
<desired_disk_usage>0.000000</desired_disk_usage>
<duration_correction_factor>1.000000</duration_correction_factor>
<sched_rpc_pending>0</sched_rpc_pending>
<send_time_stats_log>0</send_time_stats_log>
<send_job_log>0</send_job_log>
<njobs_success>21568</njobs_success>
<njobs_error>0</njobs_error>
<elapsed_time>5908199.860517</elapsed_time>
<last_rpc_time>1679620978.203934</last_rpc_time>
<dont_use_dcf/>
<dont_request_more_work/>
<rsc_backoff_time>
<name>CPU</name>
<value>0.000000</value>
</rsc_backoff_time>
<rsc_backoff_interval>
<name>CPU</name>
<value>0.000000</value>
</rsc_backoff_interval>
<no_rsc_pref>CPU</no_rsc_pref>
<rsc_backoff_time>
<name>NVIDIA</name>
<value>0.000000</value>
</rsc_backoff_time>
<rsc_backoff_interval>
<name>NVIDIA</name>
<value>0.000000</value>
</rsc_backoff_interval>
<scheduler_url>https://sech.me/boinc/Amicable_cgi/cgi</scheduler_url>
<code_sign_key>
1024
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0000000000000000000000000000000000000000000000000000000000000000
0000000000000000000000000000000000000000000000000000000000000000
0000000000000000000000000000000000000000000000000000000000000000
0000000000000000000000000000000000000000000000000000000000010001
.
</code_sign_key>
<cpu_ec>10060.331906</cpu_ec>
<cpu_time>4346063.383125</cpu_time>
<gpu_ec>183378347.647988</gpu_ec>
<gpu_time>6362591.236742</gpu_time>
<disk_usage>1180544.000000</disk_usage>
<disk_share>201244905706.899994</disk_share>
</project>
<app>
<name>amicable_10_21</name>
<user_friendly_name>Amicable Numbers up to 10^21</user_friendly_name>
<non_cpu_intensive>0</non_cpu_intensive>
</app>
<file>
<name>amicable_OpenCL_v_3_02</name>
<nbytes>1180544.000000</nbytes>
<max_nbytes>0.000000</max_nbytes>
<status>1</status>
<executable/>
<signature_required/>
<file_signature>
a351bd678b16276046e4c4a3abe38663a5f80433098a21d77927e760bf326e27
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That's a huge file, not sure what parts you need.

Thank you for taking the time to get this setup for me.

I need the <app_version> parts for Moo!, they have been cut of due to the length of the file.
Must look like that:

<app_version>
    <app_name>dnetc</app_name>
...
</app_version>

You should have few of them, under all those <file> entries.

---

Okay, I'll check when I get home from work.

OK, so run down your cache first, than:

1. Delete all files in your Moo! project dir except those 4:
dnetc_wrapper_1.5_x86_64-pc-linux-gnu__opencl_nvidia_101
dnetc521-linux-amd64-opencl
dnetc-gpu-1.3.ini
job-lin64-opencl-521.1.xml

2. Save this as app_info.xml in your Moo! project dir using a plain text editor. Make sure BOINC can read that file, Linux is a bit weird with that, I used "rw-rw-rw-" on my Android device, did not try with less that that, but r--r--r-- should also probably work:

<app_info>
 <app>
  <name>dnetc</name>
  <user_friendly_name>Distributed.net Client</user_friendly_name>
 </app>
 <file_info>
  <name>dnetc_wrapper_1.5_x86_64-pc-linux-gnu__opencl_nvidia_101</name>
  <executable/>
 </file_info>
 <file_info>
  <name>dnetc521-linux-amd64-opencl</name>
  <executable/>
 </file_info>
 <file_info>
  <name>dnetc-gpu-1.3.ini</name>
 </file_info>
 <file_info>
  <name>job-lin64-opencl-521.1.xml</name>
 </file_info>
 <app_version>
  <app_name>dnetc</app_name>
  <version_num>105</version_num>
  <avg_ncpus>0.25</avg_ncpus>
  <max_ncpus>0.25</max_ncpus>
  <plan_class>opencl_nvidia_101</plan_class>
  <platform>x86_64-pc-linux-gnu</platform>
  <coproc>
   <type>NVIDIA</type>
   <count>1</count>
  </coproc>
  <file_ref>
   <file_name>dnetc_wrapper_1.5_x86_64-pc-linux-gnu__opencl_nvidia_101</file_name>
   <main_program/>
  </file_ref>
  <file_ref>
   <file_name>dnetc521-linux-amd64-opencl</file_name>
   <copy_file/>
  </file_ref>
  <file_ref>
   <file_name>dnetc-gpu-1.3.ini</file_name>
   <open_name>dnetc.ini</open_name>
   <copy_file/>
  </file_ref>
  <file_ref>
   <file_name>job-lin64-opencl-521.1.xml</file_name>
   <open_name>job.xml</open_name>
   <copy_file/>
  </file_ref>
 </app_version>
</app_info>

3. Set your cache very low and check if it works, if not I will check the std_err of the errored out tasks. But I think I didn't miss anythink and it should work. If it doesn't work, simply shut down BOINC, delete the app_info file, start BOINC and reset the project. Or remove and add again Moo!, that clears every changes too.

The values for avg_ncpus and max_ncpus you can adjust to whatever suits your computer best, if you for example need 1 core per task, than set them both to 1. If you don't run CPU tasks at all, than they don't matter and you can leave them as they are.

---

The values for avg_ncpus and max_ncpus you can adjust to whatever suits your computer best, if you for example need 1 core per task, than set them both to 1. If you don't run CPU tasks at all, than they don't matter and you can leave them as they are.

I see your computer uses 1 whole CPU core per task, so best set avg_ncpus and max_ncpus to 1 like this:

  <avg_ncpus>1.00</avg_ncpus>
  <max_ncpus>1.00</max_ncpus>

---