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// Copyright 2015 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package ssa
import "container/heap"
const (
ScorePhi = iota // towards top of block
ScoreNilCheck
ScoreReadTuple
ScoreVarDef
ScoreMemory
ScoreDefault
ScoreFlags
ScoreControl // towards bottom of block
)
type ValHeap struct {
a []*Value
score []int8
}
func (h ValHeap) Len() int { return len(h.a) }
func (h ValHeap) Swap(i, j int) { a := h.a; a[i], a[j] = a[j], a[i] }
func (h *ValHeap) Push(x interface{}) {
// Push and Pop use pointer receivers because they modify the slice's length,
// not just its contents.
v := x.(*Value)
h.a = append(h.a, v)
}
func (h *ValHeap) Pop() interface{} {
old := h.a
n := len(old)
x := old[n-1]
h.a = old[0 : n-1]
return x
}
func (h ValHeap) Less(i, j int) bool {
x := h.a[i]
y := h.a[j]
sx := h.score[x.ID]
sy := h.score[y.ID]
if c := sx - sy; c != 0 {
return c > 0 // higher score comes later.
}
if x.Pos != y.Pos { // Favor in-order line stepping
return x.Pos.After(y.Pos)
}
if x.Op != OpPhi {
if c := len(x.Args) - len(y.Args); c != 0 {
return c < 0 // smaller args comes later
}
}
return x.ID > y.ID
}
// Schedule the Values in each Block. After this phase returns, the
// order of b.Values matters and is the order in which those values
// will appear in the assembly output. For now it generates a
// reasonable valid schedule using a priority queue. TODO(khr):
// schedule smarter.
func schedule(f *Func) {
// For each value, the number of times it is used in the block
// by values that have not been scheduled yet.
uses := make([]int32, f.NumValues())
// reusable priority queue
priq := new(ValHeap)
// "priority" for a value
score := make([]int8, f.NumValues())
// scheduling order. We queue values in this list in reverse order.
var order []*Value
// maps mem values to the next live memory value
nextMem := make([]*Value, f.NumValues())
// additional pretend arguments for each Value. Used to enforce load/store ordering.
additionalArgs := make([][]*Value, f.NumValues())
for _, b := range f.Blocks {
// Compute score. Larger numbers are scheduled closer to the end of the block.
for _, v := range b.Values {
switch {
case v.Op == OpAMD64LoweredGetClosurePtr || v.Op == OpPPC64LoweredGetClosurePtr ||
v.Op == OpARMLoweredGetClosurePtr || v.Op == OpARM64LoweredGetClosurePtr ||
v.Op == Op386LoweredGetClosurePtr || v.Op == OpMIPS64LoweredGetClosurePtr ||
v.Op == OpS390XLoweredGetClosurePtr || v.Op == OpMIPSLoweredGetClosurePtr:
// We also score GetLoweredClosurePtr as early as possible to ensure that the
// context register is not stomped. GetLoweredClosurePtr should only appear
// in the entry block where there are no phi functions, so there is no
// conflict or ambiguity here.
if b != f.Entry {
f.Fatalf("LoweredGetClosurePtr appeared outside of entry block, b=%s", b.String())
}
score[v.ID] = ScorePhi
case v.Op == OpAMD64LoweredNilCheck || v.Op == OpPPC64LoweredNilCheck ||
v.Op == OpARMLoweredNilCheck || v.Op == OpARM64LoweredNilCheck ||
v.Op == Op386LoweredNilCheck || v.Op == OpMIPS64LoweredNilCheck ||
v.Op == OpS390XLoweredNilCheck || v.Op == OpMIPSLoweredNilCheck:
// Nil checks must come before loads from the same address.
score[v.ID] = ScoreNilCheck
case v.Op == OpPhi:
// We want all the phis first.
score[v.ID] = ScorePhi
case v.Op == OpVarDef:
// We want all the vardefs next.
score[v.ID] = ScoreVarDef
case v.Type.IsMemory():
// Schedule stores as early as possible. This tends to
// reduce register pressure. It also helps make sure
// VARDEF ops are scheduled before the corresponding LEA.
score[v.ID] = ScoreMemory
case v.Op == OpSelect0 || v.Op == OpSelect1:
// Schedule the pseudo-op of reading part of a tuple
// immediately after the tuple-generating op, since
// this value is already live. This also removes its
// false dependency on the other part of the tuple.
// Also ensures tuple is never spilled.
score[v.ID] = ScoreReadTuple
case v.Type.IsFlags() || v.Type.IsTuple():
// Schedule flag register generation as late as possible.
// This makes sure that we only have one live flags
// value at a time.
score[v.ID] = ScoreFlags
default:
score[v.ID] = ScoreDefault
}
}
}
for _, b := range f.Blocks {
// Find store chain for block.
// Store chains for different blocks overwrite each other, so
// the calculated store chain is good only for this block.
for _, v := range b.Values {
if v.Op != OpPhi && v.Type.IsMemory() {
for _, w := range v.Args {
if w.Type.IsMemory() {
nextMem[w.ID] = v
}
}
}
}
// Compute uses.
for _, v := range b.Values {
if v.Op == OpPhi {
// If a value is used by a phi, it does not induce
// a scheduling edge because that use is from the
// previous iteration.
continue
}
for _, w := range v.Args {
if w.Block == b {
uses[w.ID]++
}
// Any load must come before the following store.
if !v.Type.IsMemory() && w.Type.IsMemory() {
// v is a load.
s := nextMem[w.ID]
if s == nil || s.Block != b {
continue
}
additionalArgs[s.ID] = append(additionalArgs[s.ID], v)
uses[v.ID]++
}
}
}
if b.Control != nil && b.Control.Op != OpPhi {
// Force the control value to be scheduled at the end,
// unless it is a phi value (which must be first).
score[b.Control.ID] = ScoreControl
// Schedule values dependent on the control value at the end.
// This reduces the number of register spills. We don't find
// all values that depend on the control, just values with a
// direct dependency. This is cheaper and in testing there
// was no difference in the number of spills.
for _, v := range b.Values {
if v.Op != OpPhi {
for _, a := range v.Args {
if a == b.Control {
score[v.ID] = ScoreControl
}
}
}
}
}
// To put things into a priority queue
// The values that should come last are least.
priq.score = score
priq.a = priq.a[:0]
// Initialize priority queue with schedulable values.
for _, v := range b.Values {
if uses[v.ID] == 0 {
heap.Push(priq, v)
}
}
// Schedule highest priority value, update use counts, repeat.
order = order[:0]
tuples := make(map[ID][]*Value)
for {
// Find highest priority schedulable value.
// Note that schedule is assembled backwards.
if priq.Len() == 0 {
break
}
v := heap.Pop(priq).(*Value)
// Add it to the schedule.
// Do not emit tuple-reading ops until we're ready to emit the tuple-generating op.
//TODO: maybe remove ReadTuple score above, if it does not help on performance
switch {
case v.Op == OpSelect0:
if tuples[v.Args[0].ID] == nil {
tuples[v.Args[0].ID] = make([]*Value, 2)
}
tuples[v.Args[0].ID][0] = v
case v.Op == OpSelect1:
if tuples[v.Args[0].ID] == nil {
tuples[v.Args[0].ID] = make([]*Value, 2)
}
tuples[v.Args[0].ID][1] = v
case v.Type.IsTuple() && tuples[v.ID] != nil:
if tuples[v.ID][1] != nil {
order = append(order, tuples[v.ID][1])
}
if tuples[v.ID][0] != nil {
order = append(order, tuples[v.ID][0])
}
delete(tuples, v.ID)
fallthrough
default:
order = append(order, v)
}
// Update use counts of arguments.
for _, w := range v.Args {
if w.Block != b {
continue
}
uses[w.ID]--
if uses[w.ID] == 0 {
// All uses scheduled, w is now schedulable.
heap.Push(priq, w)
}
}
for _, w := range additionalArgs[v.ID] {
uses[w.ID]--
if uses[w.ID] == 0 {
// All uses scheduled, w is now schedulable.
heap.Push(priq, w)
}
}
}
if len(order) != len(b.Values) {
f.Fatalf("schedule does not include all values")
}
for i := 0; i < len(b.Values); i++ {
b.Values[i] = order[len(b.Values)-1-i]
}
}
f.scheduled = true
}
// storeOrder orders values with respect to stores. That is,
// if v transitively depends on store s, v is ordered after s,
// otherwise v is ordered before s.
// Specifically, values are ordered like
// store1
// NilCheck that depends on store1
// other values that depends on store1
// store2
// NilCheck that depends on store2
// other values that depends on store2
// ...
// The order of non-store and non-NilCheck values are undefined
// (not necessarily dependency order). This should be cheaper
// than a full scheduling as done above.
// Note that simple dependency order won't work: there is no
// dependency between NilChecks and values like IsNonNil.
// Auxiliary data structures are passed in as arguments, so
// that they can be allocated in the caller and be reused.
// This function takes care of reset them.
func storeOrder(values []*Value, sset *sparseSet, storeNumber []int32) []*Value {
if len(values) == 0 {
return values
}
f := values[0].Block.Func
// find all stores
var stores []*Value // members of values that are store values
hasNilCheck := false
sset.clear() // sset is the set of stores that are used in other values
for _, v := range values {
if v.Type.IsMemory() {
stores = append(stores, v)
if v.Op == OpInitMem || v.Op == OpPhi {
continue
}
sset.add(v.MemoryArg().ID) // record that v's memory arg is used
}
if v.Op == OpNilCheck {
hasNilCheck = true
}
}
if len(stores) == 0 || !hasNilCheck && f.pass.name == "nilcheckelim" {
// there is no store, the order does not matter
return values
}
// find last store, which is the one that is not used by other stores
var last *Value
for _, v := range stores {
if !sset.contains(v.ID) {
if last != nil {
f.Fatalf("two stores live simultaneously: %v and %v", v, last)
}
last = v
}
}
// We assign a store number to each value. Store number is the
// index of the latest store that this value transitively depends.
// The i-th store in the current block gets store number 3*i. A nil
// check that depends on the i-th store gets store number 3*i+1.
// Other values that depends on the i-th store gets store number 3*i+2.
// Special case: 0 -- unassigned, 1 or 2 -- the latest store it depends
// is in the previous block (or no store at all, e.g. value is Const).
// First we assign the number to all stores by walking back the store chain,
// then assign the number to other values in DFS order.
count := make([]int32, 3*(len(stores)+1))
sset.clear() // reuse sparse set to ensure that a value is pushed to stack only once
for n, w := len(stores), last; n > 0; n-- {
storeNumber[w.ID] = int32(3 * n)
count[3*n]++
sset.add(w.ID)
if w.Op == OpInitMem || w.Op == OpPhi {
if n != 1 {
f.Fatalf("store order is wrong: there are stores before %v", w)
}
break
}
w = w.MemoryArg()
}
var stack []*Value
for _, v := range values {
if sset.contains(v.ID) {
// in sset means v is a store, or already pushed to stack, or already assigned a store number
continue
}
stack = append(stack, v)
sset.add(v.ID)
for len(stack) > 0 {
w := stack[len(stack)-1]
if storeNumber[w.ID] != 0 {
stack = stack[:len(stack)-1]
continue
}
if w.Op == OpPhi {
// Phi value doesn't depend on store in the current block.
// Do this early to avoid dependency cycle.
storeNumber[w.ID] = 2
count[2]++
stack = stack[:len(stack)-1]
continue
}
max := int32(0) // latest store dependency
argsdone := true
for _, a := range w.Args {
if a.Block != w.Block {
continue
}
if !sset.contains(a.ID) {
stack = append(stack, a)
sset.add(a.ID)
argsdone = false
break
}
if storeNumber[a.ID]/3 > max {
max = storeNumber[a.ID] / 3
}
}
if !argsdone {
continue
}
n := 3*max + 2
if w.Op == OpNilCheck {
n = 3*max + 1
}
storeNumber[w.ID] = n
count[n]++
stack = stack[:len(stack)-1]
}
}
// convert count to prefix sum of counts: count'[i] = sum_{j<=i} count[i]
for i := range count {
if i == 0 {
continue
}
count[i] += count[i-1]
}
if count[len(count)-1] != int32(len(values)) {
f.Fatalf("storeOrder: value is missing, total count = %d, values = %v", count[len(count)-1], values)
}
// place values in count-indexed bins, which are in the desired store order
order := make([]*Value, len(values))
for _, v := range values {
s := storeNumber[v.ID]
order[count[s-1]] = v
count[s-1]++
}
return order
}