im new to go. i have this project it's about matrices and their operations. i am supposed to use goroutine in my multiply function.(also disclaimer:this is not my code, its a group project im supposed to add the goroutine to the function)
i've searched around and seen this way(the way that i used) in different sites.however i get a fatal error: all the goroutines are asleep.deadlock!
or it just takes way too long for the code to run.
func (M Matrix) Multiply(N Matrix) Matrix {
var ans = BuildZeroMatrix(len(M), len(N[0]))
var wg sync.WaitGroup
wg.Add(len(M)*len(N[0])*len(N))
for i := 0; i < len(M); i++ {
for j := 0; j < len(N[0]); j++ {
for k := 0; k < len(N); k++ {
wg.Add(1)
go func(j int, i int, k int) {
ans[i][j] += M[i][k] * N[k][j]
defer wg.Done()
}(j, i, k)
}
}
}
go func(){
wg.Wait()
}()
return ans
}
this is the multiply function.
type Matrix [][]float64
this is Matrix.
func BuildZeroMatrix(Row int, Col int) Matrix {
var temp [][]float64
for i := 0; i < Row; i++ {
var tmp []float64
for j := 0; j < Col; j++ {
tmp = append(tmp, 0)
}
temp = append(temp, tmp)
}
M, _ := BuildMatrix(Row, Col, temp)
return M
}
and this is the buildzeromatrix function.
i give the function 2 500*500 matrices and it takes about 10 seconds to run or it gives the fatal error.
every post i found on this problem had channels in them and their problem was with the channel.however i dont have any.
Just pointing out the mistakes in this snippet. Please check the inline comments.
func (M Matrix) Multiply(N Matrix) Matrix {
var ans = BuildZeroMatrix(len(M), len(N[0]))
var wg sync.WaitGroup
wg.Add(len(M)*len(N[0])*len(N)) // This is unnecessary. You are already adding the goroutine inside the k loop.
for i := 0; i < len(M); i++ {
for j := 0; j < len(N[0]); j++ {
for k := 0; k < len(N); k++ {
wg.Add(1)
go func(j int, i int, k int) {
ans[i][j] += M[i][k] * N[k][j] // This is data race area. Multiple goroutines will try to write to the same address. You will need a lock here.
defer wg.Done()
}(j, i, k)
}
}
}
go func(){
wg.Wait() // Wait()ing for goroutines to be completed should not be done inside a goroutine. Because here you don't wait for this goroutine to be done.
}()
return ans
}
UPDATED: Pls check the sample code
package main
import (
"fmt"
"sync"
)
type Matrix [][]float64
func (M Matrix) Multiply(N Matrix) Matrix {
var ans = BuildZeroMatrix(len(M), len(N[0]))
var wg sync.WaitGroup
var mx sync.Mutex
for i := 0; i < len(M); i++ {
for j := 0; j < len(N[0]); j++ {
for k := 0; k < len(N); k++ {
wg.Add(1)
go func(j int, i int, k int) {
defer wg.Done()
mx.Lock()
ans[i][j] += M[i][k] * N[k][j]
mx.Unlock()
}(j, i, k)
}
}
}
wg.Wait()
return ans
}
func BuildZeroMatrix(Row int, Col int) Matrix {
var temp [][]float64
for i := 0; i < Row; i++ {
var tmp []float64
for j := 0; j < Col; j++ {
tmp = append(tmp, 0)
}
temp = append(temp, tmp)
}
return temp
}
func main() {
var m, n Matrix
// T1:
m = Matrix{[]float64{1, 1, 1}, []float64{1, 1, 1}, []float64{1, 1, 1}}
n = Matrix{[]float64{1, 1, 1}, []float64{1, 1, 1}, []float64{1, 1, 1}}
fmt.Printf("%v", m.Multiply(n))
// T2:
m = Matrix{[]float64{1, 1, 1}, []float64{1, 1, 1}, []float64{1, 1, 1}}
n = Matrix{[]float64{1, 1}, []float64{1, 1}, []float64{1, 1}}
fmt.Printf("\n%v", m.Multiply(n))
}
Related
im trying to implement QuickSort concurrently. When I run it and look at the sorted array, there is a portion of elements near the start of the array that is unsorted but the majority of the array is.
Code Below
package main
import (
"fmt"
"math/rand"
//"runtime"
"sync"
"time"
)
func main() {
slice := generateSlice(1000000)
var wg sync.WaitGroup
start := time.Now()
go Quicksort(slice, 0, len(slice)-1, &wg)
wg.Wait()
end := time.Since(start)
fmt.Printf("Sort Time: %v, sorted: %v \n", end, slice)
}
func Quicksort(A []int, p int, r int, wg *sync.WaitGroup) {
if p < r {
q := Partition(A, p, r)
wg.Add(2)
go Quicksort(A, p, q-1, wg)
go Quicksort(A, q+1, r, wg)
}
}
func Partition(A []int, p int, r int) int {
index := rand.Intn(r-p) + p
pivot := A[index]
A[index] = A[r]
A[r] = pivot
x := A[r]
j := p - 1
i := p
for i < r {
if A[i] <= x {
j++
tmp := A[j]
A[j] = A[i]
A[i] = tmp
}
i++
}
temp := A[j+1]
A[j+1] = A[r]
A[r] = temp
return j + 1
}
func generateSlice(size int) []int {
slice := make([]int, size)
rand.Seed(time.Now().UnixNano())
for i := 0; i < size; i++ {
slice[i] = rand.Intn(999) - rand.Intn(999)
}
return slice
}
I can't seem to find the issue, any ideas?
Your implementation has multiple problems. Hymns For Disco has already mentioned a couple of them in the comments. Another change I would suggest is not to use the same waitGroup in all recursive function calls. It can be very difficult to keep track of counter increments and decrements and you might reach a deadlock.
I have made a few changes to your code. I think it's working fine. Note that 'Partition' and 'generateSlice' functions remain unchanged.
func main() {
slice := generateSlice(1000)
Quicksort(slice, 0, len(slice)-1)
fmt.Printf("%v\n", slice)
}
func Quicksort(A []int, p int, r int) {
if p < r {
var wg sync.WaitGroup
q := Partition(A, p, r)
wg.Add(2)
go func() {
defer wg.Done()
Quicksort(A, p, q-1)
}()
go func() {
defer wg.Done()
Quicksort(A, q+1, r)
}()
wg.Wait()
}
}
I am trying to understand golang's syntax in doc but some things are hard to understand even they explain it.
For example:
func Reverse(s string) string {
r := []rune(s)
for i, j := 0, len(r)-1; i < len(r)/2; i, j = i+1, j-1 {
r[i], r[j] = r[j], r[i]
}
return string(r)
}
I translated it to raw code:
func reverseString2(str string) string {
var array = []rune(str)
for i := 0; i < len(str)/2; i++ {
for j := len(str) - 1; ???? ; j-- {
// ---
}
}
return string(array)
}
my problem is that in the first one for i, j := 0, len(r)-1; i < len(r)/2; i, j = i+1, j-1, j does not seems to have a condition so in my code I dont know how to solve it.
This is another way that is easier to read and leads to the same result.
The only difference is that the scope of variable j has become different.
func Reverse(s string) string {
r := []rune(s)
j := len(r) - 1
for i := 0; i < len(r)/2; i++ {
r[i], r[j] = r[j], r[i]
j--
}
return string(r)
}
I have a university project for testing time difference for matrix multiplication when I use 1 goroutine, 2 goroutines, 3 and so on. I must use channels. My problem is that doesn't matter how many go routines I add time of compilation is almost always the same. Maybe some one can tell where is the problem. Maybe that sending is very long and it gives all the time. Code is given below
package main
import (
"fmt"
"math/rand"
"time"
)
const length = 1000
var start time.Time
var rez [length][length]int
func main() {
const threadlength = 1
toCalcRow := make(chan []int)
toCalcColumn := make(chan []int)
dummy1 := make(chan int)
dummy2 := make(chan int)
var row [length + 1]int
var column [length + 1]int
var a [length][length]int
var b [length][length]int
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
a[i][j] = rand.Intn(10)
b[i][j] = rand.Intn(10)
}
}
for i := 0; i < threadlength; i++ {
go Calc(toCalcRow, toCalcColumn, dummy1, dummy2)
}
start = time.Now()
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
row[0] = i
column[0] = j
for k := 0; k < length; k++ {
row[k+1] = a[i][j]
column[k+1] = b[i][k]
}
rowSlices := make([]int, len(row))
columnSlices := make([]int, len(column))
copy(rowSlices, row[:])
copy(columnSlices, column[:])
toCalcRow <- rowSlices
toCalcColumn <- columnSlices
}
}
dummy1 <- -1
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
fmt.Print(rez[i][j])
fmt.Print(" ")
}
fmt.Println(" ")
}
<-dummy2
close(toCalcRow)
close(toCalcColumn)
close(dummy1)
}
func Calc(chin1 <-chan []int, chin2 <-chan []int, dummy <-chan int, dummy1 chan<- int) {
loop:
for {
select {
case row := <-chin1:
column := <-chin2
var sum [3]int
sum[0] = row[0]
sum[1] = column[0]
for i := 1; i < len(row); i++ {
sum[2] += row[i] * column[i]
}
rez[sum[0]][sum[1]] = sum[2]
case <-dummy:
elapsed := time.Since(start)
fmt.Println("Binomial took ", elapsed)
dummy1 <- 0
break loop
}
}
close(dummy1)
}
You don't see a difference because preparing the data to pass to the go routines is your bottleneck. It's slower or as fast as performing the calc.
Passing a copy of the rows and columns is not a good strategy. This is killing the performance.
The go routines may read data directly from the input matrix that are read only. There is no possible race condition here.
Same for output. If a go routine computes the multiplication of a row and a column, it will write the result in a distinct cell. There is also no possible race conditions here.
What to do is the following. Define a struct with two fields, one for the row and one for the column to multiply.
Fill a buffered channel with all possible combinations of row and columns to multiply from (0,0) to (n-1,m-1).
The go routines, consume the structs from the channel, perform the computation and write the result directly into the output matrix.
You then also have a done channel to signal to the main go routine that the computation is done. When a go routine has finished processing the struct (n-1,m-1) it closes the done channel.
The main go routine waits on the done channel after it has written all structs. Once the done channel is closed, it prints the elapsed time.
We can use a waiting group to wait that all go routine terminated their computation.
You can then start with one go routine and increase the number of go routines to see the impact of the processing time.
See the code:
package main
import (
"fmt"
"math/rand"
"sync"
"time"
)
type pair struct {
row, col int
}
const length = 1000
var start time.Time
var rez [length][length]int
func main() {
const threadlength = 1
pairs := make(chan pair, 1000)
var wg sync.WaitGroup
var a [length][length]int
var b [length][length]int
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
a[i][j] = rand.Intn(10)
b[i][j] = rand.Intn(10)
}
}
wg.Add(threadlength)
for i := 0; i < threadlength; i++ {
go Calc(pairs, &a, &b, &rez, &wg)
}
start = time.Now()
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
pairs <- pair{row: i, col: j}
}
}
close(pairs)
wg.Wait()
elapsed := time.Since(start)
fmt.Println("Binomial took ", elapsed)
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
fmt.Print(rez[i][j])
fmt.Print(" ")
}
fmt.Println(" ")
}
}
func Calc(pairs chan pair, a, b, rez *[length][length]int, wg *sync.WaitGroup) {
for {
pair, ok := <-pairs
if !ok {
break
}
rez[pair.row][pair.col] = 0
for i := 0; i < length; i++ {
rez[pair.row][pair.col] += a[pair.row][i] * b[i][pair.col]
}
}
wg.Done()
}
Your code is quite difficult to follow (calling variables dummy1/dummy2 is confusing particularly when they get different names in Calc) and adding some comments would make it more easily understood.
Firstly a bug. After sending data to be calculated you dummy1 <- -1 and I believe you expect this to wait for all calculations to be complete. However that is not necessarily the case when you have multiple goroutines. The channel will be drained by ONE of the goroutines and the timing info printed out; other goroutines will still be running (and may not have finnished their calculations).
In terms of timing I suspect that the way you are sending data to the go routines will slow things down; you send the row and then the column; because the channels are not buffered the goroutine will block while waiting for the column (switching back to the main goroutine to send the column). This back and forth will slow the rate at which your goroutines get data and may well explain why adding extra goroutines has a limited impact (it also becomes dangerous if you use buffered channels).
I have refactored your code (note there may be bugs and its far from perfect!) into something that does show a difference (on my computer 1 goroutine = 10s; 5 = 7s):
package main
import (
"fmt"
"math/rand"
"sync"
"time"
)
const length = 1000
var start time.Time
var rez [length][length]int
// toMultiply will hold details of what the goroutine will be multiplying (one row and one column)
type toMultiply struct {
rowNo int
columnNo int
row []int
column []int
}
func main() {
const noOfGoRoutines = 5
// Build up a matrix of dimensions (length) x (length)
var a [length][length]int
var b [length][length]int
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
a[i][j] = rand.Intn(10)
b[i][j] = rand.Intn(10)
}
}
// Setup completed so start the clock...
start = time.Now()
// Start off threadlength go routines to multiply each row/column
toCalc := make(chan toMultiply)
var wg sync.WaitGroup
wg.Add(noOfGoRoutines)
for i := 0; i < noOfGoRoutines; i++ {
go func() {
Calc(toCalc)
wg.Done()
}()
}
// Begin the multiplication.
start = time.Now()
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
tm := toMultiply{
rowNo: i,
columnNo: j,
row: make([]int, length),
column: make([]int, length),
}
for k := 0; k < length; k++ {
tm.row[k] = a[i][j]
tm.column[k] = b[i][k]
}
toCalc <- tm
}
}
// All of the data has been sent to the chanel; now we need to wait for all of the
// goroutines to complete
close(toCalc)
wg.Wait()
fmt.Println("Binomial took ", time.Since(start))
// The full result should be in tz
for i := 0; i < length; i++ {
for j := 0; j < length; j++ {
//fmt.Print(rez[i][j])
//fmt.Print(" ")
}
//fmt.Println(" ")
}
}
// Calc - Multiply a row from one matrix with a column from another
func Calc(toCalc <-chan toMultiply) {
for tc := range toCalc {
var result int
for i := 0; i < len(tc.row); i++ {
result += tc.row[i] * tc.column[i]
}
// warning - the below should work in this case but be careful writing to global variables from goroutines
rez[tc.rowNo][tc.columnNo] = result
}
}
I have the following code that I am to change into a concurrent program.
// Stefan Nilsson 2013-02-27
// This program creates pictures of Julia sets (en.wikipedia.org/wiki/Julia_set).
package main
import (
"image"
"image/color"
"image/png"
"log"
"math/cmplx"
"os"
"strconv"
)
type ComplexFunc func(complex128) complex128
var Funcs []ComplexFunc = []ComplexFunc{
func(z complex128) complex128 { return z*z - 0.61803398875 },
func(z complex128) complex128 { return z*z + complex(0, 1) },
}
func main() {
for n, fn := range Funcs {
err := CreatePng("picture-"+strconv.Itoa(n)+".png", fn, 1024)
if err != nil {
log.Fatal(err)
}
}
}
// CreatePng creates a PNG picture file with a Julia image of size n x n.
func CreatePng(filename string, f ComplexFunc, n int) (err error) {
file, err := os.Create(filename)
if err != nil {
return
}
defer file.Close()
err = png.Encode(file, Julia(f, n))
return
}
// Julia returns an image of size n x n of the Julia set for f.
func Julia(f ComplexFunc, n int) image.Image {
bounds := image.Rect(-n/2, -n/2, n/2, n/2)
img := image.NewRGBA(bounds)
s := float64(n / 4)
for i := bounds.Min.X; i < bounds.Max.X; i++ {
for j := bounds.Min.Y; j < bounds.Max.Y; j++ {
n := Iterate(f, complex(float64(i)/s, float64(j)/s), 256)
r := uint8(0)
g := uint8(0)
b := uint8(n % 32 * 8)
img.Set(i, j, color.RGBA{r, g, b, 255})
}
}
return img
}
// Iterate sets z_0 = z, and repeatedly computes z_n = f(z_{n-1}), n ≥ 1,
// until |z_n| > 2 or n = max and returns this n.
func Iterate(f ComplexFunc, z complex128, max int) (n int) {
for ; n < max; n++ {
if real(z)*real(z)+imag(z)*imag(z) > 4 {
break
}
z = f(z)
}
return
}
I have decided to try and make the Julia() function concurrent. So I changed it to:
func Julia(f ComplexFunc, n int) image.Image {
bounds := image.Rect(-n/2, -n/2, n/2, n/2)
img := image.NewRGBA(bounds)
s := float64(n / 4)
for i := bounds.Min.X; i < bounds.Max.X; i++ {
for j := bounds.Min.Y; j < bounds.Max.Y; j++ {
go func(){
n := Iterate(f, complex(float64(i)/s, float64(j)/s), 256)
r := uint8(0)
g := uint8(0)
b := uint8(n % 32 * 8)
img.Set(i, j, color.RGBA{r, g, b, 255})
}()
}
}
return img
This change causes the images to look very different. The patterns are essentially the same, but there are a lot of white pixels that were not there before.
What is happening here?
There are 2 problems:
You don't actually wait for your goroutines to finish.
You don't pass i and j to the goroutine, so they will almost always be the last i and j.
Your function should look something like:
func Julia(f ComplexFunc, n int) image.Image {
var wg sync.WaitGroup
bounds := image.Rect(-n/2, -n/2, n/2, n/2)
img := image.NewRGBA(bounds)
s := float64(n / 4)
for i := bounds.Min.X; i < bounds.Max.X; i++ {
for j := bounds.Min.Y; j < bounds.Max.Y; j++ {
wg.Add(1)
go func(i, j int) {
n := Iterate(f, complex(float64(i)/s, float64(j)/s), 256)
r := uint8(0)
g := uint8(0)
b := uint8(n % 32 * 8)
img.Set(i, j, color.RGBA{r, g, b, 255})
wg.Done()
}(i, j)
}
}
wg.Wait()
return img
}
A bonus tip, when diving into concurrency, it's usually a good idea to try your code with the race detector.
You might have to use a mutex to call img.Set but I'm not very sure and I can't test atm.
Can anyone comment on whether this is a reasonable and idiomatic way of implementing circular shift of integer arrays in Go? (I deliberately chose not to use bitwise operations.)
How could it be improved?
package main
import "fmt"
func main() {
a := []int{1,2,3,4,5,6,7,8,9,10}
fmt.Println(a)
rotateR(a, 5)
fmt.Println(a)
rotateL(a, 5)
fmt.Println(a)
}
func rotateL(a []int, i int) {
for count := 1; count <= i; count++ {
tmp := a[0]
for n := 1;n < len(a);n++ {
a[n-1] = a[n]
}
a[len(a)-1] = tmp
}
}
func rotateR(a []int, i int) {
for count := 1; count <= i; count++ {
tmp := a[len(a)-1]
for n := len(a)-2;n >=0 ;n-- {
a[n+1] = a[n]
}
a[0] = tmp
}
}
Rotating the slice one position at a time, and repeating to get the total desired rotation means it will take time proportional to rotation distance × length of slice. By moving each element directly into its final position you can do this in time proportional to just the length of the slice.
The code for this is a little more tricky than you have, and you’ll need a GCD function to determine how many times to go through the slice:
func gcd(a, b int) int {
for b != 0 {
a, b = b, a % b
}
return a
}
func rotateL(a []int, i int) {
// Ensure the shift amount is less than the length of the array,
// and that it is positive.
i = i % len(a)
if i < 0 {
i += len(a)
}
for c := 0; c < gcd(i, len(a)); c++ {
t := a[c]
j := c
for {
k := j + i
// loop around if we go past the end of the slice
if k >= len(a) {
k -= len(a)
}
// end when we get to where we started
if k == c {
break
}
// move the element directly into its final position
a[j] = a[k]
j = k
}
a[j] = t
}
}
Rotating a slice of size l right by p positions is equivalent to rotating it left by l − p positions, so you can simplify your rotateR function by using rotateL:
func rotateR(a []int, i int) {
rotateL(a, len(a) - i)
}
Your code is fine for in-place modification.
Don't clearly understand what you mean by bitwise operations. Maybe this
package main
import "fmt"
func main() {
a := []int{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
fmt.Println(a)
rotateR(&a, 4)
fmt.Println(a)
rotateL(&a, 4)
fmt.Println(a)
}
func rotateL(a *[]int, i int) {
x, b := (*a)[:i], (*a)[i:]
*a = append(b, x...)
}
func rotateR(a *[]int, i int) {
x, b := (*a)[:(len(*a)-i)], (*a)[(len(*a)-i):]
*a = append(b, x...)
}
Code works https://play.golang.org/p/0VtiRFQVl7
It's called reslicing in Go vocabulary. Tradeoff is coping and looping in your snippet vs dynamic allocation in this. It's your choice, but in case of shifting 10000 elements array by one position reslicing looks much cheaper.
I like Uvelichitel solution but if you would like modular arithmetic which would be O(n) complexity
package main
func main(){
s := []string{"1", "2", "3"}
rot := 5
fmt.Println("Before RotL", s)
fmt.Println("After RotL", rotL(rot, s))
fmt.Println("Before RotR", s)
fmt.Println("After RotR", rotR(rot,s))
}
func rotL(m int, arr []string) []string{
newArr := make([]string, len(arr))
for i, k := range arr{
newPos := (((i - m) % len(arr)) + len(arr)) % len(arr)
newArr[newPos] = k
}
return newArr
}
func rotR(m int, arr []string) []string{
newArr := make([]string, len(arr))
for i, k := range arr{
newPos := (i + m) % len(arr)
newArr[newPos] = k
}
return newArr
}
If you need to enter multiple values, whatever you want (upd code Uvelichitel)
package main
import "fmt"
func main() {
var N, n int
fmt.Scan(&N)
a := make([]int, N)
for i := 0; i < N; i++ {
fmt.Scan(&a[i])
}
fmt.Scan(&n)
if n > 0 {
rotateR(&a, n%len(a))
} else {
rotateL(&a, (n*-1)%len(a))
}
for _, elem := range a {
fmt.Print(elem, " ")
}
}
func rotateL(a *[]int, i int) {
x, b := (*a)[:i], (*a)[i:]
*a = append(b, x...)
}
func rotateR(a *[]int, i int) {
x, b := (*a)[:(len(*a)-i)], (*a)[(len(*a)-i):]
*a = append(b, x...)
}