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SingularityKChenSingularityKChen
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fix: correct dramToRSDataFlow; Add mapping test;
+ correct the dramToRSDataFlow's inActArray and weightArray params; + add a requirement for inActSRAMNum; + add some useful params in object mappingInfo; + add a test for variable S1 and F1;
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+137
-7
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2 files changed

+137
-7
lines changed

‎dla/tests/src/GenTestData.scala‎

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -169,9 +169,11 @@ class GenFunc(inActSparseRatio: Double = 0.845, weightSparseRatio: Double = 0.6,
169169
def dramToRSDataFlow(inActMem: Seq[Seq[List[List[Int]]]], weightMem: Seq[Seq[List[List[Int]]]]):
170170
(Seq[Seq[List[List[Int]]]], Seq[Seq[List[List[Int]]]]) = {
171171
val inActArray: Array[Array[Array[Array[Int]]]] =
172-
Array.fill(inActParNum, inActStreamNum, inActMatrixHeight, inActMatrixWidth) {0}
172+
Array.fill(p.mappingInfo.inActNoCNum, p.mappingInfo.inActGLBNum,
173+
p.mappingInfo.inActMatrixHeight, p.mappingInfo.inActMatrixWidth) {0}
173174
val weightArray: Array[Array[Array[Array[Int]]]] =
174-
Array.fill(weightParNum, weightStreamNum, weightMatrixHeight, weightMatrixWidth) {0}
175+
Array.fill(p.mappingInfo.weightNoCNum, p.mappingInfo.weightGLBNum,
176+
p.mappingInfo.weightMatrixHeight, p.mappingInfo.weightMatrixWidth) {0}
175177
for (g1 <- 0 until p.G1) {
176178
for (n1 <- 0 until p.N1) {
177179
for (m1 <- 0 until p.M1) {

‎dla/tests/src/ScalaModelTest.scala‎

Lines changed: 133 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -37,6 +37,19 @@ case class EyerissModelParam(
3737
private val inActNumInOnePEArray: Int = peRow + peCol - 1 //TODO: make it more fine grain
3838
/** the read time for one SRAM to send all the PE their inAct*/
3939
val inActSRAMReadTimes: Int = inActNumInOnePEArray/inActSRAMNum
40+
require(inActNumInOnePEArray % inActSRAMNum == 0, s"inActNumInOnePEArray = $inActNumInOnePEArray should be" +
41+
s"multiple of inActSRAMNum = $inActSRAMNum")
42+
val pSumOneSPadNum: Int = M0*E*N0*F0
43+
val inActMatrixWidth: Int = F0*N0*E // column
44+
val inActMatrixHeight: Int = R*C0 // row
45+
val weightMatrixWidth: Int = inActMatrixHeight // column
46+
val weightMatrixHeight: Int = M0 // row
47+
val inActNoCNum: Int = G1*N1*C1*(F1 + S1)
48+
val weightNoCNum: Int = G1*M1*C1*S1
49+
val pSumNoCNum: Int = G1*N1*M1*F1
50+
val weightGLBNum: Int = G2*M2*C2*S2
51+
val inActGLBNum: Int = G2*N2*C2*(F2 + S2)
52+
val pSumGLBNum: Int = G2*N2*M2*F2
4053
}
4154
object nnShape {
4255
object inAct {
@@ -88,9 +101,9 @@ class EyerissModel(sequencer: GenFunc, monitor: CompareMonitor, p: EyerissModelP
88101
) {0}
89102
private var parallelCycle = 0
90103
/** the first dimension is NoC level index, value true means have read this from mem, false means haven't read*/
91-
private val weightMemReadRecord: Array[Boolean] = Array.fill(p.G1*p.M1*p.C1*p.S1) {false}
104+
private val weightMemReadRecord: Array[Boolean] = Array.fill(p.mappingInfo.weightNoCNum) {false}
92105
/** the first dimension is NoC level index, value true means have read this from mem, false means haven't read*/
93-
private val inActMemReadRecord: Array[Boolean] = Array.fill(p.G1*p.N1*p.C1*(p.F1 + p.S1)) {false}
106+
private val inActMemReadRecord: Array[Boolean] = Array.fill(p.mappingInfo.inActNoCNum) {false}
94107
/** assume the data stored in Mem is pre-processed */
95108
/** the first dimension is cgRow idx, the second is cgCol idx, the third is inActSRAMIdx, inside is a list */
96109
private val inActAdrSRAM: Array[Array[Array[List[Int]]]] =
@@ -324,9 +337,124 @@ class CommonModel(sequencer: GenFunc, monitor: CompareMonitor, p: EyerissModelPa
324337
class ScalaModelTest extends FlatSpec {
325338
behavior of "compare the efficiency of Eyeriss"
326339
/** model the behavior of Eyeriss cluster group */
327-
/*it should "changing mapping parameters" in {
328-
329-
}*/
340+
it should "changing mapping parameters" in {
341+
object peRow {
342+
val start = 1
343+
val end = 4
344+
val during: Int = end - start
345+
}
346+
object peCol {
347+
val start = 1
348+
val end = 4
349+
val during: Int = end - start
350+
}
351+
val monitorSeq = Seq.fill(peRow.during, peCol.during, 2) {new CompareMonitor}
352+
/** the min size of inAct adr SPad and data SPad to meet the requirement.
353+
* [[SPadSizeConfig]].[[inActAdrSPadSize]] and [[SPadSizeConfig]].[[inActDataSPadSize]]*/
354+
val inActSPadSizeNeed: Array[Array[Array[Int]]] = Array.fill(peRow.during, peCol.during, 2) {0}
355+
/** the min size of inAct adr SRAM and data SRAM to meet the requirement.
356+
* [[ClusterSRAMConfig]].[[inActAdrSRAMSize]] and [[ClusterSRAMConfig]].[[inActDataSRAMSize]]*/
357+
val inActSRAMSizeNeed: Array[Array[Array[Int]]] = Array.fill(peRow.during, peCol.during, 2) {0}
358+
/** the min bits of inAct adr to meet the requirement. [[PESizeConfig]].[[inActAdrWidth]]*/
359+
val inActAdrWidthNeed: Array[Array[Int]] = Array.fill(peRow.during, peCol.during) {0}
360+
/** the min bits of inAct data to meet the requirement. [[PESizeConfig]].[[inActDataWidth]]*/
361+
val inActDataWidthNeed: Array[Array[Int]] = Array.fill(peRow.during, peCol.during) {0}
362+
/** the min size of weight adr SPad and data SPad to meet the requirement.
363+
* [[SPadSizeConfig]].[[weightAdrSPadSize]] and [[SPadSizeConfig]].[[weightDataSPadSize]]*/
364+
val weightSPadSizeNeed: Array[Array[Array[Int]]] = Array.fill(peRow.during, peCol.during, 2) {0}
365+
/** the min bits of weight adr to meet the requirement. [[PESizeConfig]].[[weightAdrWidth]]*/
366+
val weightAdrWidthNeed: Array[Array[Int]] = Array.fill(peRow.during, peCol.during) {0}
367+
/** the min bits of weight data to meet the requirement. [[PESizeConfig]].[[weightDataWidth]]*/
368+
val weightDataWidthNeed: Array[Array[Int]] = Array.fill(peRow.during, peCol.during) {0}
369+
for (peRowFactor <- peRow.start until peRow.end) {
370+
for (peColFactor <- peCol.start until peCol.end) {
371+
val peRowIdx = peRowFactor - peRow.start
372+
val peColIdx = peColFactor - peCol.start
373+
val peRowNum = 3*peRowFactor
374+
val peColNum = 4*peColFactor
375+
var readTime = 2
376+
while ((peRowNum + peColNum - 1) % readTime != 0) {
377+
readTime += 1
378+
}
379+
val inActSRAMNum = (peRowNum + peColNum - 1) / readTime
380+
val param = EyerissModelParam(peRow = peRowNum, peCol = peColNum,
381+
S1 = peRowNum, F1 = peColNum, inActSRAMNum = inActSRAMNum)
382+
val sequencer = new GenFunc(inActSparseRatio = 0.6, weightSparseRatio = 0.6, p = param)
383+
val eyerissModel = new EyerissModel(sequencer = sequencer,
384+
monitor = monitorSeq(peRowIdx)(peColIdx).head,
385+
p = param, printDetails = false)
386+
val common = new CommonModel(sequencer = sequencer,
387+
monitor = monitorSeq(peRowIdx)(peColIdx)(1),
388+
p = param, printDetails = false, needPSum = false)
389+
inActSPadSizeNeed(peRowIdx)(peColIdx)(0) =
390+
sequencer.dataSequencer.glb.separatedSPadCSCData.inActAdr.map(x => x.map(y => y.length).max).max
391+
inActSPadSizeNeed(peRowIdx)(peColIdx)(1) =
392+
sequencer.dataSequencer.glb.separatedSPadCSCData.inActData.map(x => x.map(y => y.length).max).max
393+
inActSRAMSizeNeed(peRowIdx)(peColIdx)(0) =
394+
sequencer.dataSequencer.glb.cscData.inActAdr.map(x => x.length).max
395+
inActSRAMSizeNeed(peRowIdx)(peColIdx)(1) =
396+
sequencer.dataSequencer.glb.cscData.inActData.map(x => x.length).max
397+
inActAdrWidthNeed(peRowIdx)(peColIdx) =
398+
log2Ceil(sequencer.dataSequencer.glb.cscData.inActAdr.flatten.filter(x => x != scala.math.pow(2,7)-1).max)
399+
inActDataWidthNeed(peRowIdx)(peColIdx) =
400+
log2Ceil(sequencer.dataSequencer.glb.cscData.inActData.flatten.filter(x => x != scala.math.pow(2,12)-1).max)
401+
weightSPadSizeNeed(peRowIdx)(peColIdx)(0) =
402+
sequencer.dataSequencer.glb.separatedSPadCSCData.weightAdr.map(x => x.map(y => y.length).max).max
403+
weightSPadSizeNeed(peRowIdx)(peColIdx)(1) =
404+
sequencer.dataSequencer.glb.separatedSPadCSCData.weightData.map(x => x.map(y => y.length).max).max
405+
weightAdrWidthNeed(peRowIdx)(peColIdx) =
406+
log2Ceil(sequencer.dataSequencer.glb.cscData.weightAdr.flatten.filter(x => x != scala.math.pow(2,7)-1).max)
407+
weightDataWidthNeed(peRowIdx)(peColIdx) =
408+
log2Ceil(sequencer.dataSequencer.glb.cscData.weightData.flatten.filter(x => x != scala.math.pow(2,12)-1).max)
409+
println(s"[${MAGENTA}Info$RESET] current peRow = $peRowNum, peCol = $peColNum, inActSRAM = $inActSRAMNum")
410+
if (peRowFactor == peRow.end - 1 && peColFactor == peCol.end - 1) {
411+
param.nnShape.printNNShapeInfo()
412+
param.physicalInfo.printlnPhysicalInfo()
413+
}
414+
}
415+
}
416+
println("|pRow\t|pCol\t|cycle%\t\t|mac%\t\t|iMem%\t\t|wMem%\t\t|iGLB%\t\t|iSPad%\t\t|")
417+
for (peRowFactor <- peRow.start until peRow.end) {
418+
for (peColFactor <- peCol.start until peCol.end) {
419+
val peRowIdx = peRowFactor - peRow.start
420+
val peColIdx = peColFactor - peCol.start
421+
val eyerissMonitor = monitorSeq(peRowIdx)(peColIdx).head
422+
val commonMonitor = monitorSeq(peRowIdx)(peColIdx).last
423+
val inActGLBWriteTotal = eyerissMonitor.inActWrite.adr.glb + eyerissMonitor.inActWrite.data.glb
424+
val inActGLBReadTotal = eyerissMonitor.inActRead.adr.glb + eyerissMonitor.inActRead.data.glb
425+
val inActSPadWriteTotal = eyerissMonitor.inActWrite.adr.sPad + eyerissMonitor.inActWrite.data.sPad
426+
val inActSPadReadTotal = eyerissMonitor.inActRead.adr.sPad + eyerissMonitor.inActRead.data.sPad
427+
/**inAct GLB R / GLB W */
428+
val eyerissInActGLBRW = f"${(inActGLBReadTotal.toFloat/inActGLBWriteTotal.toFloat)*100}%.2f%%"
429+
/**inAct SPad W / GLB R */
430+
val eyerissInActSPadReuse = f"${(inActSPadWriteTotal.toFloat/inActGLBReadTotal.toFloat)*100}%.2f%%"
431+
val cycleEfficiency = f"${(eyerissMonitor.cycle.toFloat / commonMonitor.cycle.toFloat)*100}%.4f%%"
432+
val macEfficiency = f"${(eyerissMonitor.macNum.toFloat / commonMonitor.macNum.toFloat)*100}%.4f%%"
433+
val inActMemReadEfficiency =
434+
f"${(eyerissMonitor.inActRead.mem.toFloat / commonMonitor.inActRead.mem.toFloat)*100}%.4f%%"
435+
val weightMemReadEfficiency =
436+
f"${(eyerissMonitor.weightRead.mem.toFloat / commonMonitor.weightRead.mem.toFloat)*100}%.4f%%"
437+
println(s"|${peRowFactor*3}\t\t|${peColFactor*4}\t\t|$cycleEfficiency\t|" +
438+
s"$macEfficiency\t|$inActMemReadEfficiency\t|$weightMemReadEfficiency\t|" +
439+
s"$eyerissInActGLBRW\t|$eyerissInActSPadReuse\t|")
440+
}
441+
}
442+
println("\n|pRow\t|pCol\t|inActAdrSPad\t|inActDataSPad\t|weightAdrSPad\t|weightDataSPad\t|inActAdrSRAM\t|inActDataSRAM\t|")
443+
for (peRowFactor <- peRow.start until peRow.end) {
444+
for (peColFactor <- peCol.start until peCol.end) {
445+
val peRowIdx = peRowFactor - peRow.start
446+
val peColIdx = peColFactor - peCol.start
447+
println(s"|${peRowFactor*3}\t\t|${peColFactor*4}\t\t|" +
448+
s"${inActSPadSizeNeed(peRowIdx)(peColIdx)(0)}\t${inActAdrWidthNeed(peRowIdx)(peColIdx)}-bit\t|" +
449+
s"${inActSPadSizeNeed(peRowIdx)(peColIdx)(1)}\t${inActDataWidthNeed(peRowIdx)(peColIdx)}-bit\t|" +
450+
s"${weightSPadSizeNeed(peRowIdx)(peColIdx)(0)}\t${weightAdrWidthNeed(peRowIdx)(peColIdx)}-bit\t|" +
451+
s"${weightSPadSizeNeed(peRowIdx)(peColIdx)(1)}\t${weightDataWidthNeed(peRowIdx)(peColIdx)}-bit\t|" +
452+
s"${inActSRAMSizeNeed(peRowIdx)(peColIdx)(0)}\t|" +
453+
s"${inActSRAMSizeNeed(peRowIdx)(peColIdx)(1)}\t|"
454+
)
455+
}
456+
}
457+
}
330458

331459
it should "compare the info across sparse ratio between eyeriss and common device" in {
332460
val param = EyerissModelParam()

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