On Thu, 17 Jun 2010 08:38:59 +0300 Orna Agmon Ben-Yehuda <ladyp...@gmail.com> wrote:
> On Wed, Jun 16, 2010 at 4:29 PM, Oleg Goldshmidt <p...@goldshmidt.org> wrote: > > > On Wed, Jun 16, 2010 at 1:23 PM, Shimon Panfil <i...@industrialphys.com> > > wrote: > > > > > > Hi folks, > > > I'm looking for affordable workstation for heavy number crunching, not > > > > What's "affordable" and what is "heavy number crunching"? > > > > For most large-scale scientific/engineering number-crunching physical > > parallelism (multiple CPUs/cores) is important for performance. Will > > you benefit from many more than 4 cores? Will anything more than > > commodity 4 core desktop be prohibitively expensive? Will you benefit > > / can you afford, e.g., a CUDA-based number-cruncher under your desk? > > > > > Note that while a CPU consumes around 100W at highest P-state (core voltage > and frequency), based for example on opteron specifications, GPGPUs consume > around 300W and even more when active. If the current box has a problem with > dissipating heat, it will not take a GPGPU. > > Furthermore, switching to GPGPU programming has a huge cost in labor. For > this specific case, in which Shimon is a consultant, my assumption is that > he works with a different piece of software every time, he will not have a > chance to enjoy the fruit of his labor. > These numbers are wrong by the way If you look here for example: http://www.guru3d.com/article/intel-core-i7-920-and-965-review/18 The difference between a medium CPU at idle (lets push it up a bit to 130W system draw when Idle) to a core i7 at 100% (lets lower it a bit to 260W at 100%) is over 130W. A low end GPU will take around 30W-40W, a high end second generation GPU (gtx 285 or tesla c1060, 240 cores, over 600GFLOPS expected, I'm not talking the peak 1TFLOP) at 100% doing cuda will run at ~160W which gives you the same delta of ~130W. The card you are talking about is the gtx 480 which has 480 cores and 1.1 TPLOP expected takes 250W, which is a larger delta but for a pretty nice jump in computing power. On the other hand, yes, if there are cooling problems now, they are going to get worse (a whole lot worse) with a GPU, the 285 can go to 80c under load and tesla to around 65c under load in a ok case with 2 external fans. On the other hand, if the cpu overheats I would investigate cpu and case issues first as that shouldn't happen (either the case is not built for the job, the heatsink is not properly connected or the fans are not up to the job or not functioning. As for the software, that is right, with gpgpu you need to write you own software, but on the otherhand, on the cpu if you are not using sse you are also under utilizing your cpu for number crunching by a factor of possibly x4-8 depending on the accuracy. And on that note, GPUs are mainly floating point machines (The new teslas 2050/2070 changed that a bit but still), so if you need double precision or random memory access or to use existing software/libraries, CPUs are still your best bet. > _______________________________________________ Linux-il mailing list Linux-il@cs.huji.ac.il http://mailman.cs.huji.ac.il/mailman/listinfo/linux-il
