From f606b5456e4876da5f90e2902b2dff07516a03dc Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Wed, 22 Aug 2018 14:52:48 +0000
Subject: [PATCH] XNOR-net 21 FPS on CPU yolov2-tiny.cfg
---
Makefile | 18 ++++++++++++++----
1 files changed, 14 insertions(+), 4 deletions(-)
diff --git a/Makefile b/Makefile
index fd76d77..ec74a81 100644
--- a/Makefile
+++ b/Makefile
@@ -2,10 +2,16 @@
CUDNN=0
CUDNN_HALF=0
OPENCV=0
-DEBUG=0
+AVX=0
OPENMP=0
LIBSO=0
+# set GPU=1 and CUDNN=1 to speedup on GPU
+# set CUDNN_HALF=1 to further speedup 3 x times (Mixed-precision using Tensor Cores) on GPU Tesla V100, Titan V, DGX-2
+# set AVX=1 and OPENMP=1 to speedup on CPU (if error occurs then set AVX=0)
+
+DEBUG=0
+
ARCH= -gencode arch=compute_30,code=sm_30 \
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=[sm_50,compute_50] \
@@ -23,8 +29,8 @@
# GP100/Tesla P100 � DGX-1
# ARCH= -gencode arch=compute_60,code=sm_60
-# For Jetson Tx1 uncomment:
-# ARCH= -gencode arch=compute_51,code=[sm_51,compute_51]
+# For Jetson TX1, Tegra X1, DRIVE CX, DRIVE PX - uncomment:
+# ARCH= -gencode arch=compute_53,code=[sm_53,compute_53]
# For Jetson Tx2 or Drive-PX2 uncomment:
# ARCH= -gencode arch=compute_62,code=[sm_62,compute_62]
@@ -50,7 +56,9 @@
ifeq ($(DEBUG), 1)
OPTS= -O0 -g
else
-CFLAGS+= -ffp-contract=fast -mavx
+ifeq ($(AVX), 1)
+CFLAGS+= -ffp-contract=fast -mavx -mavx2 -msse3 -msse4.1 -msse4.2 -msse4a
+endif
endif
CFLAGS+=$(OPTS)
@@ -86,10 +94,12 @@
CFLAGS+= -DCUDNN -I/usr/local/cudnn/include
LDFLAGS+= -L/usr/local/cudnn/lib64 -lcudnn
endif
+endif
ifeq ($(CUDNN_HALF), 1)
COMMON+= -DCUDNN_HALF
CFLAGS+= -DCUDNN_HALF
+ARCH+= -gencode arch=compute_70,code=[sm_70,compute_70]
endif
OBJ=http_stream.o gemm.o utils.o cuda.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o darknet.o detection_layer.o captcha.o route_layer.o writing.o box.o nightmare.o normalization_layer.o avgpool_layer.o coco.o dice.o yolo.o detector.o layer.o compare.o classifier.o local_layer.o swag.o shortcut_layer.o activation_layer.o rnn_layer.o gru_layer.o rnn.o rnn_vid.o crnn_layer.o demo.o tag.o cifar.o go.o batchnorm_layer.o art.o region_layer.o reorg_layer.o reorg_old_layer.o super.o voxel.o tree.o yolo_layer.o upsample_layer.o
--
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