2016-02-10 19:40:21 +00:00
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2016-02-14 14:45:52 +00:00
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# This file is used to override autotune settings
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2016-02-11 13:26:18 +00:00
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# This file is used to preset the Vector-Width, the Kernel-Accept and the Kernel-Loops Value per Device, Attack-Mode and Hash-Type
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2016-02-10 19:40:21 +00:00
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#
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# - A valid line consists of the following fields (in that order):
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# - Device-Name
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# - Attack-Mode
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# - Hash-Type
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# - Vector-Width
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# - Kernel-Accel
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# - Kernel-Loops
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2016-02-11 13:16:08 +00:00
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# - The first three columns define the filter, the other three is what is assigned when that filter matches
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2016-02-14 14:45:52 +00:00
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# - If no filter matches, autotune is used
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2016-02-10 19:40:21 +00:00
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# - Columns are separated with one or many spaces or tabs
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# - A line can not start with a space or a tab
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# - Comment lines are allowed, use a # as first character
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# - Invalid lines are ignored
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# - The Device-Name is the OpenCL Device-Name. It's shown on oclHashcat startup.
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# - If the device contains spaces, replace all spaces with _ character.
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# - The Device-Name can be assigned an alias. This is useful if many devices share the same chip
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2016-02-19 23:58:22 +00:00
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# - There's also a hard-wired Device-Name which matches all device types called:
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# - DEVICE_TYPE_CPU
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# - DEVICE_TYPE_GPU
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# - DEVICE_TYPE_ACCELERATOR
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2016-02-10 19:40:21 +00:00
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# - The use of wildcards is allowed, some rules:
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# - Wildcards can only replace an entire Device-Name, not parts just of it. eg: not Geforce_*
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# - The policy is local > global, means the closer you configure something, the more likely it is selected
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# - The policy testing order is from left to right
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# - Attack modes can be:
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# - 0 = Dictionary-Attack
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# - 1 = Combinator-Attack, will also be used for attack-mode 6 and 7 since they share the same kernel
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# - 3 = Mask-Attack
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# - The Kernel-Accel is a multiplier to OpenCL's concept of a workitem, not the workitem count
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# - The Kernel-Loops has a functionality depending on the hash-type:
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# - Slow Hash: Number of iterations calculated per workitem
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# - Fast Hash: Number of mutations calculated per workitem
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# - None of both should be confused with the OpenCL concept of a "thread", this one is maintained automatically
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# - The Vector-Width can have only the values 1, 2, 4, 8 or 'N', where 'N' stands for native, which is an OpenCl-queried data value
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# - The Kernel-Accel is limited to 1024
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# - The Kernel-Loops is limited to 1024
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2016-02-14 14:45:52 +00:00
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# - The Kernel-Accel can have 'A', where 'A' stands for autotune
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# - The Kernel-Loops can have 'A', where 'A' stands for autotune
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2016-02-10 19:40:21 +00:00
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#############
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## ALIASES ##
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#############
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2016-02-11 13:16:08 +00:00
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#Device Alias
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#Name Name
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2016-02-10 19:40:21 +00:00
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2016-05-08 11:45:49 +00:00
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Quadro_K2200 ALIAS_nv_use_simd
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Quadro_K1200 ALIAS_nv_use_simd
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Quadro_K620 ALIAS_nv_use_simd
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Quadro_M5500M ALIAS_nv_use_simd
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Quadro_M5000M ALIAS_nv_use_simd
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Quadro_M4000M ALIAS_nv_use_simd
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Quadro_M3000M ALIAS_nv_use_simd
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Quadro_K2200M ALIAS_nv_use_simd
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Quadro_M2000M ALIAS_nv_use_simd
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Quadro_M1000M ALIAS_nv_use_simd
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Quadro_K620M ALIAS_nv_use_simd
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Quadro_M600M ALIAS_nv_use_simd
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Quadro_M500M ALIAS_nv_use_simd
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NVIDIA_NVS_810 ALIAS_nv_use_simd
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GeForce_GTX_750_Ti ALIAS_nv_use_simd
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GeForce_GTX_750 ALIAS_nv_use_simd
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GeForce_GTX_960M ALIAS_nv_use_simd
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GeForce_GTX_950M ALIAS_nv_use_simd
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GeForce_GTX_940M ALIAS_nv_use_simd
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GeForce_GTX_930M ALIAS_nv_use_simd
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GeForce_GTX_850M ALIAS_nv_use_simd
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GeForce_840M ALIAS_nv_use_simd
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GeForce_830M ALIAS_nv_use_simd
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GeForce_940M ALIAS_nv_use_simd
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GeForce_930M ALIAS_nv_use_simd
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GeForce_840M ALIAS_nv_use_simd
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GeForce_830M ALIAS_nv_use_simd
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Tesla_C2050 ALIAS_nv_use_simd
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Tesla_C2050/C2070 ALIAS_nv_use_simd
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Tesla_C2070 ALIAS_nv_use_simd
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Tesla_C2075 ALIAS_nv_use_simd
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Tesla_K10 ALIAS_nv_use_simd
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Tesla_K20 ALIAS_nv_use_simd
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Tesla_K40 ALIAS_nv_use_simd
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Tesla_K80 ALIAS_nv_use_simd
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Tesla_M20xx ALIAS_nv_use_simd
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Quadro_410 ALIAS_nv_use_simd
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Quadro_K2000 ALIAS_nv_use_simd
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Quadro_K2000D ALIAS_nv_use_simd
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Quadro_K4000 ALIAS_nv_use_simd
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Quadro_K420 ALIAS_nv_use_simd
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Quadro_K4200 ALIAS_nv_use_simd
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Quadro_K5000 ALIAS_nv_use_simd
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Quadro_K5200 ALIAS_nv_use_simd
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Quadro_K600 ALIAS_nv_use_simd
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Quadro_K6000 ALIAS_nv_use_simd
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Quadro_Plex_7000 ALIAS_nv_use_simd
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NVIDIA_NVS_310 ALIAS_nv_use_simd
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NVIDIA_NVS_315 ALIAS_nv_use_simd
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NVIDIA_NVS_510 ALIAS_nv_use_simd
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NVS_310 ALIAS_nv_use_simd
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NVS_315 ALIAS_nv_use_simd
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NVS_4200M ALIAS_nv_use_simd
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NVS_510 ALIAS_nv_use_simd
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NVS_5200M ALIAS_nv_use_simd
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NVS_5400M ALIAS_nv_use_simd
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GeForce_410M ALIAS_nv_use_simd
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GeForce_610M ALIAS_nv_use_simd
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GeForce_705M ALIAS_nv_use_simd
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GeForce_710M ALIAS_nv_use_simd
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GeForce_800M ALIAS_nv_use_simd
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GeForce_820M ALIAS_nv_use_simd
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GeForce_920M ALIAS_nv_use_simd
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GeForce_GT_410M ALIAS_nv_use_simd
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GeForce_GT_415M ALIAS_nv_use_simd
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GeForce_GT_420M ALIAS_nv_use_simd
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GeForce_GT_430 ALIAS_nv_use_simd
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GeForce_GT_435M ALIAS_nv_use_simd
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GeForce_GT_440 ALIAS_nv_use_simd
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GeForce_GT_445M ALIAS_nv_use_simd
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GeForce_GT_520 ALIAS_nv_use_simd
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GeForce_GT_520M ALIAS_nv_use_simd
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GeForce_GT_520MX ALIAS_nv_use_simd
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GeForce_GT_525M ALIAS_nv_use_simd
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GeForce_GT_540M ALIAS_nv_use_simd
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GeForce_GT_550M ALIAS_nv_use_simd
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GeForce_GT_555M ALIAS_nv_use_simd
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GeForce_GT_610 ALIAS_nv_use_simd
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GeForce_GT_620 ALIAS_nv_use_simd
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GeForce_GT_620M ALIAS_nv_use_simd
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GeForce_GT_625M ALIAS_nv_use_simd
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GeForce_GT_630 ALIAS_nv_use_simd
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GeForce_GT_630M ALIAS_nv_use_simd
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GeForce_GT_635M ALIAS_nv_use_simd
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GeForce_GT_640 ALIAS_nv_use_simd
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GeForce_GT_640M ALIAS_nv_use_simd
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GeForce_GT_640M_LE ALIAS_nv_use_simd
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GeForce_GT_645M ALIAS_nv_use_simd
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GeForce_GT_650M ALIAS_nv_use_simd
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GeForce_GT_705 ALIAS_nv_use_simd
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GeForce_GT_720 ALIAS_nv_use_simd
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GeForce_GT_720M ALIAS_nv_use_simd
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GeForce_GT_730 ALIAS_nv_use_simd
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GeForce_GT_730M ALIAS_nv_use_simd
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GeForce_GT_735M ALIAS_nv_use_simd
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GeForce_GT_740 ALIAS_nv_use_simd
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GeForce_GT_740M ALIAS_nv_use_simd
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GeForce_GT_745M ALIAS_nv_use_simd
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GeForce_GT_750M ALIAS_nv_use_simd
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GeForce_GTS_450 ALIAS_nv_use_simd
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GeForce_GTX_460 ALIAS_nv_use_simd
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GeForce_GTX_460M ALIAS_nv_use_simd
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GeForce_GTX_465 ALIAS_nv_use_simd
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GeForce_GTX_470 ALIAS_nv_use_simd
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GeForce_GTX_470M ALIAS_nv_use_simd
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GeForce_GTX_480 ALIAS_nv_use_simd
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GeForce_GTX_480M ALIAS_nv_use_simd
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GeForce_GTX_485M ALIAS_nv_use_simd
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GeForce_GTX_550_Ti ALIAS_nv_use_simd
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GeForce_GTX_560M ALIAS_nv_use_simd
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GeForce_GTX_560_Ti ALIAS_nv_use_simd
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GeForce_GTX_570 ALIAS_nv_use_simd
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GeForce_GTX_570M ALIAS_nv_use_simd
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GeForce_GTX_580 ALIAS_nv_use_simd
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GeForce_GTX_580M ALIAS_nv_use_simd
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GeForce_GTX_590 ALIAS_nv_use_simd
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GeForce_GTX_610M ALIAS_nv_use_simd
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GeForce_GTX_650 ALIAS_nv_use_simd
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GeForce_GTX_650_Ti ALIAS_nv_use_simd
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GeForce_GTX_650_Ti_BOOST ALIAS_nv_use_simd
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GeForce_GTX_660 ALIAS_nv_use_simd
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GeForce_GTX_660M ALIAS_nv_use_simd
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GeForce_GTX_660_Ti ALIAS_nv_use_simd
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GeForce_GTX_670 ALIAS_nv_use_simd
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GeForce_GTX_670M ALIAS_nv_use_simd
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GeForce_GTX_670MX ALIAS_nv_use_simd
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GeForce_GTX_675M ALIAS_nv_use_simd
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GeForce_GTX_675MX ALIAS_nv_use_simd
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GeForce_GTX_680 ALIAS_nv_use_simd
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GeForce_GTX_680M ALIAS_nv_use_simd
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GeForce_GTX_680MX ALIAS_nv_use_simd
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GeForce_GTX_690 ALIAS_nv_use_simd
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GeForce_GTX_705M ALIAS_nv_use_simd
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GeForce_GTX_710M ALIAS_nv_use_simd
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GeForce_GTX_760 ALIAS_nv_use_simd
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GeForce_GTX_760M ALIAS_nv_use_simd
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GeForce_GTX_765M ALIAS_nv_use_simd
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GeForce_GTX_770 ALIAS_nv_use_simd
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GeForce_GTX_770M ALIAS_nv_use_simd
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GeForce_GTX_780 ALIAS_nv_use_simd
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GeForce_GTX_780M ALIAS_nv_use_simd
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GeForce_GTX_780_Ti ALIAS_nv_use_simd
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GeForce_GTX_800M ALIAS_nv_use_simd
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GeForce_GTX_820M ALIAS_nv_use_simd
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GeForce_GTX_860M ALIAS_nv_use_simd
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GeForce_GTX_870M ALIAS_nv_use_simd
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GeForce_GTX_880M ALIAS_nv_use_simd
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GeForce_GTX_920M ALIAS_nv_use_simd
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GeForce_GTX_TITAN ALIAS_nv_use_simd
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GeForce_GTX_TITAN_Black ALIAS_nv_use_simd
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GeForce_GTX_TITAN_Z ALIAS_nv_use_simd
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2016-02-13 15:07:58 +00:00
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2016-02-10 19:40:21 +00:00
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#############
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## ENTRIES ##
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#############
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2016-05-07 13:50:18 +00:00
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DEVICE_TYPE_CPU * * N A A
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2016-05-07 17:44:02 +00:00
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DEVICE_TYPE_CPU * 6100 1 A A
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DEVICE_TYPE_CPU * 6900 1 A A
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2016-02-10 19:40:21 +00:00
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2016-02-13 15:07:58 +00:00
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#Device Attack Hash Vector Kernel Kernel
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#Name Mode Type Width Accel Loops
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2016-02-10 19:40:21 +00:00
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2016-05-08 11:45:49 +00:00
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ALIAS_nv_use_simd * * 1 A A
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ALIAS_nv_use_simd * 0 4 A A
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ALIAS_nv_use_simd * 11 4 A A
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ALIAS_nv_use_simd * 12 4 A A
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ALIAS_nv_use_simd * 21 2 A A
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ALIAS_nv_use_simd * 22 2 A A
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ALIAS_nv_use_simd * 23 2 A A
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ALIAS_nv_use_simd * 30 4 A A
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ALIAS_nv_use_simd * 200 4 A A
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ALIAS_nv_use_simd * 400 2 A A
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ALIAS_nv_use_simd * 900 4 A A
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ALIAS_nv_use_simd * 1000 4 A A
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ALIAS_nv_use_simd * 1100 2 A A
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ALIAS_nv_use_simd * 2400 2 A A
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ALIAS_nv_use_simd * 2410 2 A A
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ALIAS_nv_use_simd * 2600 2 A A
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ALIAS_nv_use_simd * 2611 2 A A
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ALIAS_nv_use_simd * 2612 2 A A
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ALIAS_nv_use_simd * 2711 2 A A
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ALIAS_nv_use_simd * 2811 2 A A
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ALIAS_nv_use_simd * 3711 2 A A
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ALIAS_nv_use_simd * 5100 2 A A
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ALIAS_nv_use_simd * 5500 2 A A
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ALIAS_nv_use_simd * 9900 4 A A
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ALIAS_nv_use_simd * 10100 2 A A
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ALIAS_nv_use_simd * 11000 2 A A
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ALIAS_nv_use_simd * 11100 2 A A
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2016-02-10 19:40:21 +00:00
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2016-02-19 23:58:22 +00:00
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##############
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## OSX Iris ##
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##############
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2016-02-13 15:07:58 +00:00
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2016-02-19 23:58:22 +00:00
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Iris * * 1 A 2
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Iris * 400 1 A 256
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Iris * 500 1 8 256
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Iris * 501 1 8 256
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Iris * 1500 1 A 256
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Iris * 1600 1 8 256
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Iris * 1800 1 1 16
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Iris * 2100 1 8 256
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Iris * 2500 1 2 256
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Iris * 3000 1 A 256
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Iris * 5200 1 8 256
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Iris * 5800 1 8 256
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Iris * 6211 1 8 200
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Iris * 6212 1 8 200
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Iris * 6213 1 8 200
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Iris * 6221 1 4 200
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Iris * 6222 1 4 200
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Iris * 6223 1 4 200
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Iris * 6231 1 4 200
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Iris * 6232 1 4 200
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Iris * 6233 1 4 200
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Iris * 6241 1 4 200
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Iris * 6242 1 4 200
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Iris * 6243 1 4 200
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Iris * 6300 1 8 256
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Iris * 6400 1 8 256
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Iris * 6500 1 8 256
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Iris * 6600 1 8 200
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Iris * 6700 1 8 256
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Iris * 6800 1 2 200
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Iris * 7100 1 1 256
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Iris * 7200 1 1 200
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Iris * 7400 1 2 200
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Iris * 7900 1 1 256
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Iris * 8800 1 8 256
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Iris * 8900 1 1 1
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Iris * 9000 1 2 16
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Iris * 9100 1 4 256
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Iris * 9200 1 1 200
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Iris * 9300 1 1 1
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Iris * 9400 1 1 200
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Iris * 9500 1 1 200
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Iris * 9600 1 1 200
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Iris * 10000 1 1 200
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Iris * 10300 1 8 128
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Iris * 10500 1 4 64
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Iris * 10900 1 2 200
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Iris * 11300 1 1 1
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Iris * 11600 1 1 512
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Iris * 11900 1 2 200
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Iris * 12000 1 2 200
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Iris * 12100 1 2 200
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Iris * 12200 1 1 256
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Iris * 12300 1 2 256
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Iris * 12400 1 1 256
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Iris * 12500 1 1 256
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Iris * 12700 1 64 10
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Iris * 12800 1 64 100
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Iris * 12900 1 8 64
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Iris * 13000 1 1 64
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