Difference between revisions of "MachineList"

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You can connect to the machines using their complete domain name, such as squid2.math.cornell.edu
 
The easiest way to connect to these machines is through the [[Math Portal]].
 
'''Offsite Cloud Machines'''
 
In addition to the machines below, it's now possible to launch a fully-configured Math machine, with all software, licenses, and access to your files, at cloud providers such as Cornell Center for Advanced Computing, or Amazon AWS. These machines appear on the Math network just like other Math machines and are accessed in the same way. These cloud machines can be very large and fast, or include top of the line GPUs. The cloud machines are pay-as-you-go, rounded up to the next hour. For always-on computers like the ones at the Math department, these cloud machines would be very expensive. However, for fixed-duration use, they can be a fantastic bargain. Eventually there will be a self-service page for this, but for now, if you want more information about using Cloud computing resources, email mathsystems@cornell.edu.
 
'''Dedicated Computation Machines'''
{| class="wikitable" border="1"
|Hostname ||Processor ||Cores / Threads ||RAM ||GPU ||Net
|-
|ramsey || i7-6700AMD CPURyzen @9 3.40GHz5950x || 416/432 || 64GB128GB || N/ARTX 3080Ti || 10Gb
|-
|fibonacci|| i7-6700 CPUAMD @Ryzen 3.40GHz9 5950x || 416/832 || 64GB128GB || N/ARTX 3080Ti || 10Gb
|-
|heavisideboole|| Xeon AMD E5-2640Ryzen 9 5950x || 1216/2432 || 256GB128GB || N/ARTX 3080Ti || 10Gb
|-
 
|hopper||Xeon E5-2640 || 16/32 ||256GB || N/A
|pacioli squid1|| i7-37706700k CPU @ 34.40GHz0GHz || 4/8 || 16GB64GB || N/ARTX 2080 Ti || 10Gb
|-
|nautilus squid2|| Xeoni7-6700k X5560CPU @ 4.0GHz || 84/168 || 96GB64GB || N/ARTX 2080 Super || 10Gb
|-
|kraken|| Quad Opteron || 64/64 || 512GB || N/A|| 1Gb
|-
|heaviside|| Xeon E5-2640 || 12/24 || 256GB || N/A || 10Gb
|-
|hopper||Xeon E5-2640 || 16/32 ||256GB || N/A || 10Gb
 
|}
 
 
'''SharedVirtual WorkstationsMachines'''
 
These are virtual machines made available with extra resources from the department servers.<br>
NOTE: These machines are available but their memory and cpu count are subject to change.
{| border="1"
|Hostname ||Processor ||Cores / ThreadsvCores ||RAM ||GPU ||Net
|-
|conway || VM on AMD Epyc Milan || 14 || 64GB || N/A ||10Gb
|-
|dynkin || VM on AMD Epyc Milan || 14 || 64GB || N/A ||10Gb
|}
 
 
'''Private Machines'''
 
These machines are the property of faculty members and may only be used with their permission.
{| border="1"
|Hostname ||Processor ||Cores / Threads ||RAM ||GPU ||Net ||Owner
|-
|leo || Xeon E5-2698 || 40/80 || 256GB || N/A || 10Gb || A. Townsend
|-
|wooster || AMD Ryzen 9 5950x || 16/32 || 128GB || RTX 3080Ti || 1Gb || D. Barbasch
|-
|blanchzeno || i7-4790 CPUAMD @Ryzen 3.60GHz9 5950x || 416/832 || 8GB128GB || RTX 3080Ti || 10Gb || N/A. Vladimirsky
|-
|pacioli || i7-3770 CPU @ 3.40GHz || 4/8 || 16GB || N/A
|-
|kleene || i7-3770 CPU @ 3.40GHz ||4/8 || 16GB || N/A
|}

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