From 3e5abe0680c6112c9674204c22db7bd4b238d2b5 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Tue, 20 Mar 2018 00:14:20 +0000
Subject: [PATCH] Update Readme.md
---
Makefile | 17 +++++++++++------
1 files changed, 11 insertions(+), 6 deletions(-)
diff --git a/Makefile b/Makefile
index f8bd4a5..41f0e04 100644
--- a/Makefile
+++ b/Makefile
@@ -9,18 +9,23 @@
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=[sm_50,compute_50] \
-gencode arch=compute_52,code=[sm_52,compute_52] \
- -gencode arch=compute_61,code=[sm_61,compute_61]
+ -gencode arch=compute_61,code=[sm_61,compute_61]
+# Tesla V100
+# ARCH= -gencode arch=compute_70,code=[sm_70,compute_70]
+
+# GTX 1080, GTX 1070, GTX 1060, GTX 1050, GTX 1030, Titan Xp, Tesla P40, Tesla P4
+# ARCH= -gencode arch=compute_61,code=sm_61 -gencode arch=compute_61,code=compute_61
+
+# 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 Tx2 uncomment:
+# For Jetson Tx2 or Drive-PX2 uncomment:
# ARCH= -gencode arch=compute_62,code=[sm_62,compute_62]
-# This is what I use, uncomment if you know your arch and want to specify
-# ARCH= -gencode arch=compute_52,code=compute_52
-
VPATH=./src/
EXEC=darknet
@@ -69,7 +74,7 @@
LDFLAGS+= -L/usr/local/cudnn/lib64 -lcudnn
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 super.o voxel.o tree.o
+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
ifeq ($(GPU), 1)
LDFLAGS+= -lstdc++
OBJ+=convolutional_kernels.o activation_kernels.o im2col_kernels.o col2im_kernels.o blas_kernels.o crop_layer_kernels.o dropout_layer_kernels.o maxpool_layer_kernels.o network_kernels.o avgpool_layer_kernels.o
--
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