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CS/COE 0449 static data
Creation date：2024-05-30 16:58:14
Belonging category：计算机computer science
static data

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CS/COE 0449
Introduction to
Systems SoftwareManagement
6
Memory
Our Story So Far
You Hear a Voice Whisper: “The Memory Layout is a Lie”
2
Reallocating our thoughts
• A program has several sections:
• Code
• Static data
• Stack
• Heap
• Today, we take a deeper dive at how dynamic
memory is allocated in the heap.
3
currently unused but
available memory
code
static data
heap
stack
~ 0xFFFFFFFF
~ 0x00000000
Potential Layout
(32-bit addresses)
Reallocating our thoughts
• We have looked at malloc and calloc.
• They stake out space in the heap and return an
address.
• Right now, we live in a nice ideal world.
• No other programs are running.
• We have access to all of the memory.
• Muhahahaha!!
• The OS is lying to our program.
• This memory is… virtual... reality.
• We will investigate this lie later in the course.
4
currently unused but
available memory
code
static data
heap
stack
~ 0xFFFFFFFF
~ 0x00000000
Potential Layout
(32-bit addresses)
The World of Allocation
It is a puzzle without any optimal solution. Welcome to computers!
5
A heap of possibilities
• Stack access often does not deviate much.
• We allocate a little bit at a time.
• We allocate and free the memory VERY often.
• Heap allocations have many access patterns that are
possible.
• You might allocate a lot at a time and keep it around for a
long time. Or a short time.
• You might allocate a lot of small things, instead.
• Maybe you do a little bit of everything?
• Often, such patterns are not easy to predict.
• Do you get a big file as input? A small file?
6
currently unused but
available memory
code
static data
heap
stack
~ 0xFFFFFFFF
~ 0x00000000
Potential Layout
(32-bit addresses)
available memory
available memory
available memory
A heaping helping of good luck
• Allocations could happen in a nice order.
• When something is allocated, it can be allocated
after everything else.
• When freed, it makes room for new things.
• IF ONLY.
• I mean, it’s possible… but like…
• the heap and stack are different things for a reason.
7
code
static data
heap
stack
~ 0x00000000
available memoryavailable memory
available memoryavailable memory
Digital potholes… as annoying as real ones
• Small allocations interfere with large ones.
• When small gaps interfere with allocation, this is
called fragmentation.
8
available memory
code
static data
heap
stack
~ 0x00000000
?
Next
Allocation
Ugh
Ugh U
gh
free()
malloc()
if we had omniscience of future
allocations, we could avoid this…
but we can’t know ahead of time!
The worst case
• When you allocate a lot of small things…
• Free every other one…
• And then attempt to allocate a bigger thing…
• Even though there is technically enough memory…
• There is no continuous space.
• Therefore, our naïve malloc will fail.
• We have to come up with some strategy.
9
code
static data
heap
stack
~ 0x00000000
malloc() ? ? ?
Moving is never easy
• Why not move things around??
• A defragmentation process/algorithm
• Moving around something in the heap is hard!
• Any pointers referring to data within a block must be updated.
• Finding these pointers automatically is effectively as difficult
as garbage collection.
• Because of this, moving blocks around is discouraged.
(Easier to solve it another way.)
10
code
static data
heap
stack
~ 0x00000000
malloc() ? ? ?
Moving is NEVER easy
• When blocks move, pointers
to anything within them must be updated.
• This is hard to keep track of!
• C does not check validity of pointers after free()
11
available memory
code
static data
heap
stack
~ 0x00000000
int* my_int
float* my_float
3.14-1.8e-6
42?????
old data: int arr[100]
Stressing it out
• If we allocate a large array it will be allocated on the
heap somewhere.
• Other allocations can also happen, and they go “above”
that array.
• What happens when you need to append a 101st
element to this array?
• Uh oh!
• You will need to allocate more space.
• And then copy the array contents.
• Free the old array.
• How long does that take?
12
available memory
heap
stack
~ 0x00000000
int rr[100]
int arr[200]
fragmentation
old data: int arr[100]
Stressing it out: Big Arrays
• This happens in very practical situations!
• Reallocating means getting rid of a small thing
• And replacing it with a larger thing.
• You could have TiBs of memory and this will be a problem.
• This affects performance: (in terms of writes:)
• Appending item arr[0]: 1
• Appending item arr[1]: 1
• …
• Appending item arr[99]: 1
• Appending item arr[100]: + 1 oh no!
• When you would overflow the buffer…
• You then need to copy all previous values as well.
13
available memory
heap
stack
~ 0x00000000
int rr[100]
old data: int arr[100]
Stressing it out: Performance Consistency
• Big arrays want to be continuous.
• Ensuring continuous space is difficult when you do not know
how much you will ultimately need.
• This is exactly why linked lists exist!
• Since a linked list allocates on every append.
• Each append takes the same amount of time.
• However, everything is a trade-off.
• Dang it!!!
• One cost is extra overhead for metadata.
• Linked list traversal can stress memory caches.
• It means traversing the array is slower.
• However, we will mostly ignore this for now. 14
available memory
heap
stack
~ 0x00000000
int rr[100]
The Linked List
A story about trade-offs.
15
What is a linked list?
• A linked list is a non-continuous data structure representing an ordered list.
• Each item in the linked list is represented by metadata called a node.
• This metadata indirectly refers to the actual data.
• Furthermore, it indirectly refers to at least one other item in the list.
16
Node
Node* next
char* data
typedef struct _Node {
struct _Node* next;
char* data;
} Node; “struct” required since
Node is not technically
defined until after it is
defined!
Keeping ahead of the list.
• Creation of a list occurs when one allocates a single node and tracks it in a
pointer. This is the head of our list (first element.)
17
Node
Node* next
char* data
Node* list
Node* list = (Node*)malloc(sizeof(Node));
list->next = NULL; // NULL is our end-of-list marker
list->data = NULL; // Allocate/copy the data you want
Adding some links to our chain
• If we want to append an item, we can add a node anywhere!
18
“tail”
Node* next
char* data
Node* list
void append(Node* tail, const char* value) {
Node* node = (Node*)malloc(sizeof(Node));
node->next = NULL; // The new end of our list
tail->next = node; // We attach this node to the old last node
node->data = (char*)malloc(strnlen(value, 100) + 1);
strncpy(node->data, value, 100);
}
“node”
Node* next
char* data
Remember the
‘\0’ sentinel!
This is a problem!
Why?
We can add them anywhere!!
• Consider what happens if we update our append to take any Node:
19
void linkedListAppend(Node* curNode, const char* value) {
Node* node = (Node*)malloc(sizeof(Node));
node->next = curNode->next;
curNode->next = node;
node->data = (char*)malloc(strnlen(value, 100) + 1);
strcpy(node->data, value);
}
“curNode”
Node* next
char* data
Node* list
Tail
Node* next
char* data
“node”
Node* next
char* data
We can add them anywhere!!
• This function has very consistent performance (constant time):
• The append always allocates the same amount.
• It always copies the same amount.
• Compare to a big array where you may have to copy the entire thing to
append something new!
void linkedListAppend(Node* curNode, const char* value) {
Node* node = (Node*)malloc(sizeof(Node));
node->next = curNode->next;
curNode->next = node;
node->data = (char*)malloc(strnlen(value, 100) + 1);
strcpy(node->data, value);
}
Traversal… on the other hand…
• Accessing an array element is generally very simple.
• arr[42] is the same as *(arr + 42) because its location is very well-known!
• This is because array items are continuous in memory. Not true for linked lists!
• Here is a function that performs the equivalent for linked lists:
21
Node* linkedListGet(Node* head, size_t index) {
Node* curNode = head;
while(curNode && index) {
index--;
curNode = curNode->next;
}
return curNode;
}
Q: How many times is memory accessed relative to the requested index?
Removing… on the other, other hand!
• One nice thing about linked lists
is their flexibility to changing
shape.
• I used to be able to bend a lot
better, too, when I was in my 20s.
Alas.
• Since we don’t have a way to go
“backward”
• We first find the node we want to
delete (curNode)
• Keeping track of the node of index
– 1 (lastNode)
• Rewire lastNode to cut out
curNode.
22
Node* linkedListDelete(Node* head, size_t index) {
Node* lastNode = NULL;
Node* curNode = head;
while(curNode && index) {
index--;
lastNode = curNode;
curNode = curNode->next;
}
if (!curNode)
return head;
if (!lastNode)
head = curNode->next; // New head is next item
else
lastNode->next = curNode->next; // Orphans item
free(curNode->data);
free(curNode);
return head;
} Returns new head (or old head if unchanged).
Can’t find item at index.
We are deleting the head.
Removing… on the other, other hand!
• This looks complex, but it really is
a simple traversal.
• So it takes to find the item.
• And it performs a simple update
and deallocation. (quick to do)
• A big array, on the other hand.
• It can find the element to remove
immediately.
• However, removing it means
shifting over every item after it left.
• That can be an expensive update!
(Memory is slow!!)
23
Node* linkedListDelete(Node* head, size_t index) {
Node* lastNode = NULL;
Node* curNode = head;
while(curNode && index) {
index--;
lastNode = curNode;
curNode = curNode->next;
}
if (!curNode)
return head;
if (!lastNode)
head = curNode->next; // New head is next item
else
lastNode->next = curNode->next; // Orphans item
free(curNode->data);
free(curNode);
return head;
}
On your own!
Think about the code you would need to do any of the following:
• Delete/free the entire linked list.
• Sort a linked list.
• Append a linked list to an existing one.
• Copy a subset of a linked list to a new list.
Often, operations can be abstracted in such a way that all of these can be written relatively
simply.
Consider the performance of these operations compared to an Array.
24
Linked lists … link you … to the world!
• Consider how much cleaner you can make certain operations if you tracked the
previous node as well.
• This is a doubly linked list.
• This is typically “double-ended” as well: keeping track of both head and tail.
25
Node
Node* next
char* data
Node* prev
Node
Node* next
char* data
Node* prev
Node
Node* next
char* data
Node* prevNode*head
Node*
tail
Seeing the trees through the forest
• A binary tree can be represented by the same nodes as a linked list.
• In this case, you have a left and right child node instead of next and prev.
• The operations are
very different, though.
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A PHIL2617 PHYS3116 MIE250 BCPM0008 ECN 620 QBUS6830 ECSE-415 ECON5102 MGMT20005 MAT 653 ECO 480 COMP 5/600 CSSE 5600 ME 571 7CCMMS61 CS 550 COMP2865 MATH3075 STATS 506 QTM 220 ISYS2120 FIT5106 STAT 153 MKTG3112 ECON2102 ELE2018 COMP3031 MSIN0010 SCC461 MATH237 CS246 CSC3065 CSE 101 ICTWEB411 COMP9313 ECOS 2025 FN620 MATH11111 MATH 3018 KE1068 FINA 6112 C++ MISM 6202 MSIN0105 CSC8631 MECO6935 COMP4121 ACCT2011 DPBS1150 EEL 3701C F19PL OPM 661 CSE 310 CS918 BIOL30001 ACCT3563 BANK3600 MET CS622 MATH367 ACCT5907 Continuing COMP5048 COMP61021 CS3334 GSOE9210 CSCI-570 COMP 5322 HW 2 ALY-6020 IEOR 4706 DATA 200 EBUS504 CGE12412 COMP4108 7SSMM800 ECMM171P MATE50002 CS225 RS 6003 BH2274 ELEC3111 MAT6669 ECON-UA 227 PHIL 1012 7SSMM603 TB028A P6 ECS708 CSC 427 CS6476 CSE 250A A1A2 ITS61504 EECS 376 model HW6 UV0010 ECON 6074 MG4F7 CMP-7030Y INFO3008 BFIP013 ECON 5068 MATH6002 CS3483 PSTAT 131 C31FM CSOR W4246 AAEC 5307 DATA ELEC362 COMSM0047 ECN6006 MA20224 BST351 MATH 323 MATH323 AA2021 COMP3811 COMP2013 IB9X60 INVP001 EMATM0051 COMP220 BLAW1002 E20 TCP8001 ECON61001 EART40005 ECONM1022 MATH 365 MATH 367 ELEC6218 COMP 5812M EDUC 5061M ELEC ENG 1101 equation MATH6174 ST334 C4 EC9570 A33648 EBUS603 ECON47815 stata WFMS0001 PEM102 INF6060 ionically ELECTRICAL MATH 375 MMW 12 MKTG860 ECON60401 ALY6010 SOST20131 Introduction COM3524 MME2 GGR305 JNB 538 EECS101 COMM5030 IEOR E4601 2B CSC336 EN2315 LAW 432 CSC263 MATH2001 OLET1143 CSCB63 SIT772 COMM1170 STAT 441 MS930 INFT3050 GLBH0030 Stat 120B MAST10007 MGEC61 Machine GGR 252H1S ECON7030 Financial Marketing MGMT30019 ECON5120 SDSC 8009 CSC165H1S DSCI 551 3081W ACM41000 ECA 5304 MATH 1064 ECSE444 DATA 604 COMP7105 MIE1615 ECON4004 ENV200H1S EC481 MKT 306 EC1B1 MATH08051 ALY6140 CS260C CSE30 MSIN0226 CS4103 CSC3064 AM16 COMP11212 CSE4101 PSTAT 174 Math 380W CNT 5106C STAT 310 FIN2028 CS5014 STAT 425 COMP 4102A ELEC2140 MANF9544 QRM 9 QRM 8 ECON 457 COMPSCI 4091 MATH 523 DNSC-4211 PEAS 6000 MSIN0180 COMP2119 A2A HT 2022 IB93F0 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COMSM0093 COMP281 AFM 333 IBUS1001 CP2501 Math 105A VE320 TEC101 SOCY2166 COM240 EFIM20033 ENGI4467 EFIM20034 EC 979 BE432 7EJ502 CSSE6400 COMP90025 Econ 312 ENG2031 ECO0006 EXERSCI 207 CAN209 ECO 137W FT312 ECO 2199 MATH32052 BDW4213 APS 360 SAS 6 CHME0017 PO92Q Economics 01AV MATH39512 MATH 5486 COMP8620 ISE102 ECON235 ECON 206 FI 345 PHAY0020 MATH0099 MATH0085 EFB106 PHY 134 MAE115 circuits Chemistry CSE12 MATH-UA 233 PHAS0038 COMP2140 CONMGNT 7049 COMP151101 ECON 485 ACX5903 ENGN6536 ARCH1162 Law PHAS0042 CCF1C03 MATH 351 Phys 139 AG942 MGT001371 APH106 ECON1051 MA4AM MA3Z7 NUMBER THEORY REST0006 SESS0026 STAT0023 TABL 2741 CMP4008Y EFIM10015 Acct 560 PSYC735 GEOG 5 ACCT3104 CSEC5616 PHIL1012 ITLS6111 ECON8022 5CCM226A compX123 MA4XJ R001 EWB LLP120 COMP643 ENG 103 ECON 23950 ACCT 207 FINC 616 Bio99 Math 137A Psychology BCPM0054 MATH20212 EC3450 CENV6141 PSY 205 CE335 CS365 Calculus ACSD INFT6800 MCIT INFO6030 PHYS 111LV H63EEJ ECON2151 ENGI 2181 MTRX1701 PLIT08009 CS240 Math 270 CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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