PATCH] Suricata: drop unused cuda HW acceleration

PATCH] Suricata: drop unused cuda HW acceleration

[Peter Müller]

[-- Attachment #1: Type: text/plain, Size: 2442 bytes --]

As stated in https://bugzilla.ipfire.org/show_bug.cgi?id=11808#c5 ,
Cuda hardware acceleration is unused and so the configuration file
section can be removed.

This partially addresses #11808.

Signed-off-by: Peter Müller <peter.mueller(a)link38.eu>
Cc: Stefan Schantl <stefan.schantl(a)ipfire.org>
---
 config/suricata/suricata.yaml | 35 -----------------------------------
 1 file changed, 35 deletions(-)

diff --git a/config/suricata/suricata.yaml b/config/suricata/suricata.yaml
index 94e13f501..55b6c05cf 100644
--- a/config/suricata/suricata.yaml
+++ b/config/suricata/suricata.yaml
@@ -933,41 +933,6 @@ profiling:
     filename: pcaplog_stats.log
     append: yes
 
-##
-## Hardware accelaration
-##
-
-# Cuda configuration.
-cuda:
-  # The "mpm" profile.  On not specifying any of these parameters, the engine's
-  # internal default values are used, which are same as the ones specified in
-  # in the default conf file.
-  mpm:
-    # The minimum length required to buffer data to the gpu.
-    # Anything below this is MPM'ed on the CPU.
-    # Can be specified in kb, mb, gb.  Just a number indicates it's in bytes.
-    # A value of 0 indicates there's no limit.
-    data-buffer-size-min-limit: 0
-    # The maximum length for data that we would buffer to the gpu.
-    # Anything over this is MPM'ed on the CPU.
-    # Can be specified in kb, mb, gb.  Just a number indicates it's in bytes.
-    data-buffer-size-max-limit: 1500
-    # The ring buffer size used by the CudaBuffer API to buffer data.
-    cudabuffer-buffer-size: 500mb
-    # The max chunk size that can be sent to the gpu in a single go.
-    gpu-transfer-size: 50mb
-    # The timeout limit for batching of packets in microseconds.
-    batching-timeout: 2000
-    # The device to use for the mpm.  Currently we don't support load balancing
-    # on multiple gpus.  In case you have multiple devices on your system, you
-    # can specify the device to use, using this conf.  By default we hold 0, to
-    # specify the first device cuda sees.  To find out device-id associated with
-    # the card(s) on the system run "suricata --list-cuda-cards".
-    device-id: 0
-    # No of Cuda streams used for asynchronous processing. All values > 0 are valid.
-    # For this option you need a device with Compute Capability > 1.0.
-    cuda-streams: 2
-
 ##
 ## Include other configs
 ##
-- 
2.16.4