Kind of necessary when running SETI MB, but also Einsteins B.P.Search. Milkyway GPU work is short (66 sec on my 5870s)but very high usage %, load reaches ~100% especially when you have freed 1 or 2 cores to control the GPUs. In my experience you can run Einstein Binary Pulsar Search for AMD/ATI & NVidia GPUs and MB also AstroPulse both on 1 GPU, each using 1/2 GPU. SETI uses Single Pecision, not sure about Einsteins GPU apps.But think the are I suspect it has something to do with the douple precision math used by MW. For now I run a single instance of MW on the gpu even though two will run together with better performance. BPR4's that take 35 minutes go to 4 hours when run with a MW task. I would like to get some indication about whether this problem (single task requiring multi-GPU resource) is known to developers and if there had been some work done about it before I jump on it.Quote: Is there a way to tell BOINC not to mix tasks from different applications on a gpu running multiple wu's? I run Einstein, Seti and MilkWay and mixing MilkyWay with any other application kills the performance of the other app. I probably should compile BOINC CC on my own. I already tried to run newer BOINC CC but I'm unable to use Berkeley-provided executable - my OS distribution is somehow elderly so system libraries are too old. However, as this project is only a wrapper around different type of distributed computing project, it's not totally in hands of project management to make needed changes to the crunching (I just can't call it science) application. There's some discussion on Moo! boards about making dnetc application nicer - so that it would only occupy designated GPU and not all of them. This is far from ideal as both tasks want to run on both GPUs. If I edit client_state.xml and decrease count of CUDA for Moo! to 1.0, BOINC CC starts a couple of Moo! tasks. As BOINC CC decided NVIDIA resources were not ample enough, both GPUs stayed idle. However, during this tests I disabled Einstein so it's only Moo! that wants to use NVIDIA. I don't have proper CUDA application for Seti (yet, see problem description right at the end of this post), Einstein provides with nice CUDA application. On this host I have multiple projects running: CPDN, Seti, Einstein and now Moo!. However BOINC CC claims that my system doesn't have enough NVIDIA GPUs available:Ġ 13:30:53 insufficient NVIDIA for dnetc_r72_1330613363_72_192_0 Project scheduler this correctly indicates by setting coproc count to 2.0. Their science application grabs all available GPUs. One example is project Moo! Wrap, which is a wrapper for DNETC projects. If this gets larger than 1.0, then it doesn't work at all. Tasks requiring NVIDIA coprocessor run fine until their requirement is 1.0. BOINC CC sees them just fine:Ġ 13:30:51 Starting BOINC client version 7.0.2 for x86_64-pc-linux-gnuĠ 13:30:51 This a development version of BOINC and may not function properlyĠ 13:30:51 log flags: file_xfer, sched_ops, task, coproc_debug, cpu_sched, cpu_sched_debugĠ 13:30:51 Libraries: libcurl/7.18.2 OpenSSL/0.9.8g zlib/1.2.3.3 libidn/1.8 libssh2/0.18Ġ 13:30:51 Data directory: censoredĠ 13:30:51 Processor: 8 AuthenticAMD Dual-Core AMD Opteron(tm) Processor 8218 Ġ 13:30:51 Processor: 1.00 MB cacheĠ 13:30:51 Processor 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 rdtscp lm 3dnowext 3dnow rep_good extd_apicid pni cx16 lahf_lm cmp_legacy svm extapic cr8_legacyĠ 13:30:51 Memory: 63.05 GB physical, 56.83 GB virtualĠ 13:30:51 Disk: 66.40 GB total, 20.64 GB freeĠ 13:30:51 Local time is UTC +0 hoursĠ 13:30:51 NVIDIA GPU 0: GeForce GT 430 (driver version unknown, CUDA version 4.20, compute capability 2.1, 1024MB, 1001MB available, 280 GFLOPS peak)Ġ 13:30:51 NVIDIA GPU 1: GeForce GT 430 (driver version unknown, CUDA version 4.20, compute capability 2.1, 1024MB, 1001MB available, 280 GFLOPS peak)Ġ 13:30:51 OpenCL: NVIDIA GPU 0: GeForce GT 430 (driver version 295.20, device version OpenCL 1.1 CUDA, 1024MB)Ġ 13:30:51 OpenCL: NVIDIA GPU 1: GeForce GT 430 (driver version 295.20, device version OpenCL 1.1 CUDA, 1024MB)Ġ 13:30:51 NVIDIA library reports 2 GPUs I've recently installed two video cards in my Linux box.
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