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University of Illinois, Urbana Champaign *
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Course
5755
Subject
Electrical Engineering
Date
Dec 6, 2023
Type
Pages
5
Uploaded by DukeIce5246 on coursehero.com
Name:
Carlos Suberviola
NetID:
cls383
Course:
ECE 5755
Lab 1:
1. Profiling:
a. convolution():
b. relu():
0%
20%
40%
60%
80%
100%
in_size(18)
in_size(9)
in_size(2048)
Convolution
Frontend_Bound
Bad_Speculation
Backend_Bound
Retiring
0%
20%
40%
60%
80%
100%
in_size(3)
in_size(15)
in_size(1088)
ReLU
Frontend_Bound
Bad_Speculation
Backend_Bound
Retiring
c. linear():
d. matmul():
0%
20%
40%
60%
80%
100%
in_size(6)
in_size(24)
in_size(1008)
Linear
Frontend_Bound
Bad_Speculation
Backend_Bound
Retiring
0%
20%
40%
60%
80%
100%
in_size(4)
in_size(36)
in_size(1024)
Matmul
Frontend_Bound
Bad_Speculation
Backend_Bound
Retiring
e. softmax():
In general, as input sizes became larger, the retiring rate increased, the
frontend bound rate decreased, and bad speculation decreased. This is most
pronounced in the matmul() and convolution() functions. Since the retiring rate
is a measure of how quickly the CPU can complete instructions and the
frontend bound rate is a measure of how much time the CPU spends waiting
for instructions to be fetched and decoded, this means that the code ran more
efficiently as the input size increased. Bad speculation also decreased, which
means that less unnecessary operations were performed when larger inputs
were provided. Since the backend bound does not change noticeably, the main
bottlenecks are in the backend, likely due to long operations or because the
memory system is inherently slow.
2. Function Implementation:
a. convolution():
The convolution function iterates over all filters (numFilters) and all channels
(numChannels). It then iterates over all output pixels (i, j), and calculates
the weighted sum of the input pixels in the kernel area. Next, it adds up the
channels per filter. Finally, it adds the bias term and applies the ReLU
activation function.
b. relu():
If value is greater than 0, return value. Else, return 0.
0%
20%
40%
60%
80%
100%
in_size(3)
in_size(10)
in_size(1280)
Softmax
Frontend_Bound
Bad_Speculation
Backend_Bound
Retiring
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