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  • I need to buy a server

    In my lab, we have two server already. We usually use DNASTAR to make assembly or mapping on the second one. And we use GoldenHelix and Partek on the first one. Because we do not know a lot about Linux, so we all use windows system. I by my self has install a virtual Ubuntu to use some software. Now my boss ask me to order a new server/workstation. The budget is about 10K and we hope we can get more powerful machine than we already have. As a freshman in this realm, I come here to ask everyone's advice. Thank you!
    The first one:
    CPU: i7-4770K 3.5GHz 8 core
    RAM: 32G
    DISK: ATA Samsung SSD 840 SCSI Disk Device
    Intel Raid 0 Volume SCSI Disk Device
    Display: NVIDIA Geforce GTX 760
    IDE ATA/ATAPI controllers:Asmedia 106x SATA Controller
    ATA Channel 0
    ATA Channel 1
    Storage controller: Intel(R) Desktop/Workstation/Server Express Chipset SATA RAID Controller

    The second one:
    CPU: Dual Intel Xeon E5 2670, 16 core each
    RAM: 96G
    DISK: DELL PERC H310 SCSI DISK Device
    Display: Standard VGA Graphics Adapter
    IDE ATA/ATAPI controllers: Standard AHCI 1.0 Serial ATA Controller
    ATA Channel 0-5
    Storage controller: PERC H310 Adapter

  • #2
    What is the intended application for the new server/workstation?

    Comment


    • #3
      Originally posted by GenoMax View Post
      What is the intended application for the new server/workstation?
      Will also be like DNASTAR, GoldenHelix, R, Notepad++, NextGEne and mach1 or minimac and so on. I have suggest my boss to install a Unix system.

      Comment


      • #4
        Does not sound like your needs include NGS data analysis. If that is the case you will be fine with either of those configs.

        Comment


        • #5
          Hi, I'm head of engineering at Golden Helix so can answer with some experience on at least that use case.

          There are three things to trade-off resources at a server config:

          - CPU (cores and speed)
          - Memory
          - Disk

          I didn't see your disk config, bug given the potential applications I think you need a RAID5 with 3x 4TB drives ~10TB of usable space, which takes up a large chunk of your budget already.

          If you are doing alignment etc you may need the 96GB of RAM, but you won't for our software. 16GB should be plenty. But maybe high-mem is a requirement which fixes you there as well.

          On CPU, the big question is whether you can parallelize a lot of analysis across many cores. I would suspect you can some, but a lot of things will be single-threaded bound and it makes sense to go for a faster GHz vs core count. So a 4 or 6 core (which is really 8-12 hyperthreaded) would be fine with a high GHz.

          Comment


          • #6
            Originally posted by gaberudy View Post
            Hi, I'm head of engineering at Golden Helix so can answer with some experience on at least that use case.

            There are three things to trade-off resources at a server config:

            - CPU (cores and speed)
            - Memory
            - Disk

            I didn't see your disk config, bug given the potential applications I think you need a RAID5 with 3x 4TB drives ~10TB of usable space, which takes up a large chunk of your budget already.

            If you are doing alignment etc you may need the 96GB of RAM, but you won't for our software. 16GB should be plenty. But maybe high-mem is a requirement which fixes you there as well.

            On CPU, the big question is whether you can parallelize a lot of analysis across many cores. I would suspect you can some, but a lot of things will be single-threaded bound and it makes sense to go for a faster GHz vs core count. So a 4 or 6 core (which is really 8-12 hyperthreaded) would be fine with a high GHz.

            Sorry for not indicating the disk room. The first one is 250GB for SSD and 4TB for RAID 0. The second one is 3x 8TB drives ~21TB of usable space.

            Comment


            • #7
              Originally posted by GenoMax View Post
              Does not sound like your needs include NGS data analysis. If that is the case you will be fine with either of those configs.
              We still have some problems when doing the mapping of the whole genome sequence data mapping. We think possibly owing to the RAM. Besides, when doing imputation, the RAM always ran out.

              Comment


              • #8
                For extra "burst" memory, you can use SSD drives (with ideally a PCIe or NVMe interface) as swap, which will allow you to do assembly without completely hosing a desktop computer.

                Comment


                • #9
                  Long-read sequencing has enabled the de novo assembly of several mammalian genomes, but with high cost in computing. Here, we demonstrated de novo assembly of mammalian genome using long reads in an efficient and inexpensive workstation.

                  A $4,000 Workstation for Mammalian Genome Assembly with Long Reads
                  "Long-read sequencing has enabled the de novo assembly of several mammalian genomes, but with high cost in computing. Here, we demonstrated de novo assembly of mammalian genome using long reads in an efficient and inexpensive workstation."

                  Comment


                  • #10
                    Yes, Canu is a wonderful piece of software; very nice for long-read assembly.

                    Comment


                    • #11
                      We just got ourselves a new Supermicro-based workstation:
                      • 2xE5-2620v4
                      • 128GB DDR4 RAM
                      • 1TB SSD+2x4TB HDD
                      • GeForce GT 730

                      Less than £4,000, including a 24" IPS monitor.

                      For 10K USD you can buy an very powerful workstation. As was already mentioned, you will need to adjust the specifications to match your needs. For example, if you aim to do assemblies of large data sets, you want to have as much RAM and storage space as possible, CPU speed and # of cores will be less important. If you mainly run multithreaded programs that benefit from increased CPU clock speed, then invest in better processors. SSD/NVMe will be a good addition, but I would prioritise RAM amount over larger SSDs (a single 512GB SSD should be enough for the system disk). If you work with NGS data sets, having lots of backed-up storage space (HDDs) would never harm.

                      As for the OS, we use Ubuntu on the workstation and CentOS on our HPC, but if you feel more comfortable with Windows or the majority of the programs you use are Windows-only, then stick with Windows. You will be able to run Linux and Windows on the same machine in a dual-boot configuration, or run Linux in a virtual machine or use Docker. The performance overhead of virtualisation is not that dramatic.

                      Comment


                      • #12
                        We just got ourselves a new Supermicro-based workstation:
                        • 2xE5-2620v4
                        • 128GB DDR4 RAM
                        • 1TB SSD+2x4TB HDD
                        • GeForce GT 730

                        Less than £4,000, including a 24" IPS monitor.

                        For 10K USD you can buy an very powerful workstation. As was already mentioned, you will need to adjust the specifications to match your needs. For example, if you aim to do assemblies of large data sets, you want to have as much RAM and storage space as possible, CPU speed and # of cores will be less important. If you mainly run multithreaded programs that benefit from increased CPU clock speed, then invest in better processors. SSD/NVMe will be a good addition, but I would prioritise RAM amount over larger SSDs (a single 512GB SSD should be enough for the system disk). If you work with NGS data sets, having lots of backed-up storage space (HDDs) would never harm.

                        As for the OS, we use Ubuntu on the workstation and CentOS on our HPC, but if you feel more comfortable with Windows or the majority of the programs you use are Windows-only, then stick with Windows. You will be able to run Linux and Windows on the same machine in a dual-boot configuration, or run Linux in a virtual machine or use Docker. The performance overhead of virtualisation is not that dramatic.

                        Comment


                        • #13
                          I think you need more RAM.
                          I have a workstation with more RAM and less CPU power.
                          • 2x E5-2640 v4
                          • 512GB DDR4 RAM
                          • 400GB SSD + 2x3TB HDD
                          • GTX 1070 for calculation with CUDA


                          They were just 9,000 USD. I didn't have any problems from TSA projects to WGS projects with genome size under 800 mb.

                          Comment

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