cluster:107
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cluster:107 [2012/12/19 14:54] hmeij [ConfCall & Quote: MW] |
cluster:107 [2013/01/16 15:20] hmeij [ConfCall & Quote: MW] |
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| * buy a single rack and test locally, start small (will future racks be compatible? | * buy a single rack and test locally, start small (will future racks be compatible? | ||
| + | |||
| + | ==== Yale Qs ==== | ||
| + | |||
| + | Tasked with getting GPU HPC going at Wesleyan and trying to gain insights into the project. If you acquired a GPU HPC ... | ||
| + | |||
| + | * What was the most important design element of the cluster? | ||
| + | * What factor(s) settled the CPU to GPU ratio? | ||
| + | * Was either, or neither, single or double precision peak performance more/less important? | ||
| + | * What was the software suite in mind (commercial, | ||
| + | * How did you reach out/educate users on the aspects of GPU computing? | ||
| + | * What was the impact on the users? (recoding, recompiling) | ||
| + | * Was the expected computational speed up realized? | ||
| + | * Was the PGI Accelerator compilers leveraged? If so what were the results? | ||
| + | * Do users compile with nvcc? | ||
| + | * Does the scheduler have a resource for idle GPUs so they can be reserved? | ||
| + | * How are the GPUs exposed/ | ||
| + | * Do you allow multiple serial jobs to access the same GPU? Or one parallel job multiples GPUs? | ||
| + | * Can parallel jobs access mutliple GPUs across nodes? | ||
| + | * Any experiences with pmemd.cuda.MPI (part of Amber)? | ||
| + | * What MPI flavor is used most in regards to GPU computing? | ||
| + | * Do you leverage the CPU HPC of the GPU HPC? For example, if there are 16 GPUs and 64 CPU cores on a cluster, do you allow 48 standard jobs on the idle cores? (assuming the max of 16 serial GPU jobs) | ||
| + | |||
| + | Notes 04/01/2012 ConfCall | ||
| + | |||
| + | * Applications drive the CPU-to-GPU ratio and most will be 1-to-1, certainly not larger then 1-to-3 | ||
| + | * Users did not share GPUs but could obtain more than one, always on same node | ||
| + | * Experimental setup with 36 gb/node, dual 8 core chips | ||
| + | * Nothing larger than that memory wise as CPU and GPU HPC work environments were not mixed | ||
| + | * No raw code development | ||
| + | * Speed ups was hard to tell | ||
| + | * PGI Accelerator was used because it is needed with any Fortran code (Note!) | ||
| + | * Double precision was most important in scientific applications | ||
| + | * MPI flavor was OpenMPI, and others (including MVApich) showed no advantages | ||
| + | * Book: Programming Massively Parallel Processors, Second Edition: | ||
| + | * A Hands-on Approach by David B. Kirk and Wen-mei W. Hwu (Dec 28, 2012) | ||
| + | * Has examples of how to expose GPUs across nodes | ||
| ==== ConfCall & Quote: AC ==== | ==== ConfCall & Quote: AC ==== | ||
| Line 321: | Line 357: | ||
| ^ Topic^Description | ^ Topic^Description | ||
| - | | General| 2 CPUs (16 cores), 3 GPUs ( 22,500 cuda cores), 32 gb ram/node| | + | | General| 2 CPUs (16 cores), 3 GPUs ( 7,500 cuda cores), 32 gb ram/node| |
| | Head Node| None| | | Head Node| None| | ||
| | Nodes|1x4U Rackmountable Chassis, 2xXeon E5-2660 2.20 Ghz 20MB Cache 8 cores (16cores/ | | Nodes|1x4U Rackmountable Chassis, 2xXeon E5-2660 2.20 Ghz 20MB Cache 8 cores (16cores/ | ||
| Line 571: | Line 607: | ||
| | | 5x upgrade to 64 GB per node| | | | 5x upgrade to 64 GB per node| | ||
| - | * At full load 5,900 Watts, 20,131 BTUs/ | + | * At full load 5,900 Watts and 20,131 BTUs/ |
| * 2% more expansive than " | * 2% more expansive than " | ||
| Line 577: | Line 613: | ||
| * With lifetime technical support | * With lifetime technical support | ||
| * solid state drives on compute nodes | * solid state drives on compute nodes | ||
| + | * 12 TB local storage | ||
| Then | Then | ||
| Line 582: | Line 619: | ||
| * 36 port FDR switch replace with 8 port QDR switch for savings (40 vs 56 Gbps) | * 36 port FDR switch replace with 8 port QDR switch for savings (40 vs 56 Gbps) | ||
| * and all server adapter cards to QDR (with one hook up to existing Voltaire switch) | * and all server adapter cards to QDR (with one hook up to existing Voltaire switch) | ||
| - | * Execute the Upgrade packages | + | * Expand memory footprint |
| - | * We could go to 124 GB memory | + | * Go to 124 GB memory/noe to beef up the CPU HPC side of things |
| - | * 16 cpu cores/nodes-4 cpu/gpu cores/ | + | * 16 cpu cores/ |
| * Online testing available (K20, do this) | * Online testing available (K20, do this) | ||
| * then decide on PGI compiler at purchase time | * then decide on PGI compiler at purchase time | ||
| * maybe all Lapack libraries too | * maybe all Lapack libraries too | ||
| - | * Make the head node a compute node (in/for the future and beef it up too) | + | * Make the head node a compute node (in/for the future and beef it up too, 256 GB ram?) |
| - | * Remove | + | * Leave the 6x2TB disk space (for backup) |
| + | * 2U, 8 drives up to 6x4=24 TB, possible? | ||
| + | * Add an entry level Infiniband/ | ||
| + | * for parallel file locking | ||
| + | |||
| + | * Spare parts | ||
| + | * 8 port switch, HCAs and cables, drives ... | ||
| + | * or get 5 years total warranty | ||
| + | * Testing notes | ||
| + | * Amber, LAMMPS, NAMD | ||
| + | * cuda v4&5 | ||
| + | * install/ | ||
| + | * use gnu ... with openmpi | ||
| + | * make deviceQuery | ||
| \\ | \\ | ||
| **[[cluster: | **[[cluster: | ||
cluster/107.txt · Last modified: 2013/09/11 13:18 by hmeij
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