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Posted to commits@systemml.apache.org by mb...@apache.org on 2018/08/03 05:52:31 UTC
[1/3] systemml git commit: [SYSTEMML-2480] Fix codegen register
allocation special cases
Repository: systemml
Updated Branches:
refs/heads/master 180c4f281 -> 8fbeca142
[SYSTEMML-2480] Fix codegen register allocation special cases
This patch fixes special cases of codegen register allocation which
(1) computed an incorrect initial count due to missing suport for Nary
operations, and (2) incorrectly reported valid configurations for probes
of count 1 and 0 because the sequence generator does not support these
small cycles.
Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/b3b50c00
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/b3b50c00
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/b3b50c00
Branch: refs/heads/master
Commit: b3b50c0047b95143719411b3937d9f5ab42c7397
Parents: 180c4f2
Author: Matthias Boehm <mb...@gmail.com>
Authored: Thu Aug 2 19:45:37 2018 -0700
Committer: Matthias Boehm <mb...@gmail.com>
Committed: Thu Aug 2 22:54:03 2018 -0700
----------------------------------------------------------------------
.../apache/sysml/hops/codegen/template/TemplateUtils.java | 10 ++++++++--
1 file changed, 8 insertions(+), 2 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/systemml/blob/b3b50c00/src/main/java/org/apache/sysml/hops/codegen/template/TemplateUtils.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/hops/codegen/template/TemplateUtils.java b/src/main/java/org/apache/sysml/hops/codegen/template/TemplateUtils.java
index f2ad7e6..8b6db37 100644
--- a/src/main/java/org/apache/sysml/hops/codegen/template/TemplateUtils.java
+++ b/src/main/java/org/apache/sysml/hops/codegen/template/TemplateUtils.java
@@ -47,6 +47,7 @@ import org.apache.sysml.hops.codegen.cplan.CNode;
import org.apache.sysml.hops.codegen.cplan.CNodeBinary;
import org.apache.sysml.hops.codegen.cplan.CNodeBinary.BinType;
import org.apache.sysml.hops.codegen.cplan.CNodeData;
+import org.apache.sysml.hops.codegen.cplan.CNodeNary;
import org.apache.sysml.hops.codegen.cplan.CNodeTernary;
import org.apache.sysml.hops.codegen.cplan.CNodeUnary;
import org.apache.sysml.hops.codegen.cplan.CNodeUnary.UnaryType;
@@ -409,7 +410,9 @@ public class TemplateUtils
public static boolean isUnaryOperatorPipeline(CNode node) {
if( node.isVisited() ) {
//second reference to vector intermediate invalidates a unary pipeline
- return !(node instanceof CNodeBinary && ((CNodeBinary)node).getType().isVectorPrimitive());
+ return !((node instanceof CNodeBinary && ((CNodeBinary)node).getType().isVectorPrimitive())
+ || (node instanceof CNodeTernary && ((CNodeTernary)node).getType().isVectorPrimitive())
+ || (node instanceof CNodeNary && ((CNodeNary)node).getType().isVectorPrimitive()));
}
boolean ret = true;
for( CNode input : node.getInput() )
@@ -452,7 +455,9 @@ public class TemplateUtils
&& ((CNodeUnary)node).getType().isVectorScalarPrimitive()) ? 1 : 0;
int cntTn = (node instanceof CNodeTernary
&& ((CNodeTernary)node).getType().isVectorPrimitive()) ? 1 : 0;
- return ret + cntBin + cntUn + cntTn;
+ int cntNn = (node instanceof CNodeNary
+ && ((CNodeNary)node).getType().isVectorPrimitive()) ? 1 : 0;
+ return ret + cntBin + cntUn + cntTn + cntNn;
}
public static int getMaxLiveVectorIntermediates(CNode node, CNode main, Map<Long, Set<Long>> parents, Set<Pair<Long, Long>> stack) {
@@ -479,6 +484,7 @@ public class TemplateUtils
}
public static boolean isValidNumVectorIntermediates(CNode node, CNode main, Map<Long, Set<Long>> parents, Map<Long, Pair<Long, MutableInt>> inUse, Set<Long> inUse2, int count) {
+ if( count <= 1 ) return false;
IDSequence buff = new IDSequence(true, count-1); //zero based
inUse.clear(); inUse2.clear();
node.resetVisitStatus();
[3/3] systemml git commit: [MINOR] Performance / cleanup conv2d R
test script (vectorized biasadd)
Posted by mb...@apache.org.
[MINOR] Performance / cleanup conv2d R test script (vectorized biasadd)
Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/8fbeca14
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/8fbeca14
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/8fbeca14
Branch: refs/heads/master
Commit: 8fbeca142c1fbb8f2786a1097fb9840be5ca8005
Parents: fce9d97
Author: Matthias Boehm <mb...@gmail.com>
Authored: Thu Aug 2 22:53:30 2018 -0700
Committer: Matthias Boehm <mb...@gmail.com>
Committed: Thu Aug 2 22:54:13 2018 -0700
----------------------------------------------------------------------
src/test/scripts/functions/tensor/Conv2DTest.R | 15 +++++----------
1 file changed, 5 insertions(+), 10 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/systemml/blob/8fbeca14/src/test/scripts/functions/tensor/Conv2DTest.R
----------------------------------------------------------------------
diff --git a/src/test/scripts/functions/tensor/Conv2DTest.R b/src/test/scripts/functions/tensor/Conv2DTest.R
index dbe9ea4..41ae7ed 100644
--- a/src/test/scripts/functions/tensor/Conv2DTest.R
+++ b/src/test/scripts/functions/tensor/Conv2DTest.R
@@ -105,19 +105,14 @@ conv2d <- function(X, W, C, Hin, Win, Hf, Wf, strideh, stridew, padh, padw) {
out
}
-output = conv2d(x, w, numChannels, imgSize, imgSize, filterSize, filterSize, stride, stride, pad, pad);
+R = conv2d(x, w, numChannels, imgSize, imgSize, filterSize, filterSize, stride, stride, pad, pad);
Hout = as.integer((imgSize + 2 * pad - filterSize) / stride + 1)
Wout = Hout
-b=matrix(seq(1, numFilters), numFilters, 1, byrow=TRUE)
+b = matrix(seq(1, numFilters), numFilters, 1, byrow=TRUE)
for(k in 0:(numFilters-1)) {
- for(i in 1:nrow(output)) {
- start = k*Hout*Hout;
- for(j in 1:(Hout*Hout)) {
- output[i,start+j] = output[i,start+j] + b[k+1,1]
- }
- }
+ start = k*Hout^2;
+ R[,(start+1):(start+Hout^2)] = R[,(start+1):(start+Hout^2)] + b[k+1,1]
}
-
-writeMM(as(output,"CsparseMatrix"), paste(args[8], "B", sep=""))
+writeMM(as(R,"CsparseMatrix"), paste(args[8], "B", sep=""))
[2/3] systemml git commit: [SYSTEMML-2067] Codegen support for
im2col/conv2d DNN operations
Posted by mb...@apache.org.
[SYSTEMML-2067] Codegen support for im2col/conv2d DNN operations
This patch adds codegen support in row templates for DNN conv2d
operations. Specially, we generated row-wise im2col and conv2d-mm
operations, which allows for CSE of im2col if multiple conv2d operations
are fused into the same row-wise operator.
Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/fce9d978
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/fce9d978
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/fce9d978
Branch: refs/heads/master
Commit: fce9d978d00bf5d42d6be9a475dee346e1844e00
Parents: b3b50c0
Author: Matthias Boehm <mb...@gmail.com>
Authored: Thu Aug 2 22:16:23 2018 -0700
Committer: Matthias Boehm <mb...@gmail.com>
Committed: Thu Aug 2 22:54:08 2018 -0700
----------------------------------------------------------------------
src/main/java/org/apache/sysml/hops/DnnOp.java | 26 ++---
.../sysml/hops/codegen/cplan/CNodeNary.java | 95 +++++++++++++---
.../hops/codegen/template/TemplateRow.java | 23 ++--
.../runtime/codegen/LibSpoofPrimitives.java | 38 ++++++-
.../runtime/matrix/data/LibMatrixDNNIm2Col.java | 7 +-
.../runtime/matrix/data/LibMatrixMult.java | 7 +-
.../functions/codegen/RowAggTmplTest.java | 29 ++++-
.../codegen/RowConv2DOperationsTest.java | 5 +-
.../scripts/functions/codegen/rowAggPattern46.R | 107 +++++++++++++++++++
.../functions/codegen/rowAggPattern46.dml | 43 ++++++++
10 files changed, 326 insertions(+), 54 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/main/java/org/apache/sysml/hops/DnnOp.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/hops/DnnOp.java b/src/main/java/org/apache/sysml/hops/DnnOp.java
index 3b48371..4e22f59 100644
--- a/src/main/java/org/apache/sysml/hops/DnnOp.java
+++ b/src/main/java/org/apache/sysml/hops/DnnOp.java
@@ -601,15 +601,13 @@ public class DnnOp extends MultiThreadedHop
|| op == OpOpDnn.CONV2D
|| op == OpOpDnn.CONV2D_BACKWARD_FILTER
|| op == OpOpDnn.CONV2D_BACKWARD_DATA) {
- imageHeightHop = getInput().get(8);
- filterHeightHop = getInput().get(12);
_cachedParams.setIfUnknown(
getInput().get(6), // N
getInput().get(7), // C
- imageHeightHop, // H
+ getInput().get(8), // H
getInput().get(9), // W
getInput().get(10), // K
- filterHeightHop, // R
+ getInput().get(12), // R
getInput().get(13), // S
getInput().get(2), // stride_h
getInput().get(3), // stride_w
@@ -617,19 +615,17 @@ public class DnnOp extends MultiThreadedHop
getInput().get(5), _maxNumThreads);
}
else {
- imageHeightHop = getInput().get(7);
- filterHeightHop = getInput().get(11);
_cachedParams.setIfUnknown(
getInput().get(5),
- getInput().get(6),
- imageHeightHop,
- getInput().get(8),
- getInput().get(9),
- filterHeightHop,
- getInput().get(12),
- getInput().get(1),
- getInput().get(2),
- getInput().get(3),
+ getInput().get(6),
+ getInput().get(7),
+ getInput().get(8),
+ getInput().get(9),
+ getInput().get(11),
+ getInput().get(12),
+ getInput().get(1),
+ getInput().get(2),
+ getInput().get(3),
getInput().get(4), _maxNumThreads);
}
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/main/java/org/apache/sysml/hops/codegen/cplan/CNodeNary.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/hops/codegen/cplan/CNodeNary.java b/src/main/java/org/apache/sysml/hops/codegen/cplan/CNodeNary.java
index e720601..28e47f4 100644
--- a/src/main/java/org/apache/sysml/hops/codegen/cplan/CNodeNary.java
+++ b/src/main/java/org/apache/sysml/hops/codegen/cplan/CNodeNary.java
@@ -33,7 +33,9 @@ public class CNodeNary extends CNode
public enum NaryType {
VECT_CBIND,
VECT_MAX_POOL,
- VECT_AVG_POOL;
+ VECT_AVG_POOL,
+ VECT_IM2COL,
+ VECT_CONV2DMM;
public static boolean contains(String value) {
for( NaryType bt : values() )
@@ -63,18 +65,30 @@ public class CNodeNary extends CNode
}
return sb.toString();
case VECT_MAX_POOL:
- case VECT_AVG_POOL:
+ case VECT_AVG_POOL: {
String vectName = (this==VECT_MAX_POOL) ? "Maxpool" : "Avgpool";
- String paramStr = getPoolingParameterString(inputs);
+ String paramStr = getDnnParameterString(inputs, true);
return sparseGen ?
" double[] %TMP% = LibSpoofPrimitives.vect"+vectName+"Write(%IN1v%, %IN1i%, %POS1%, alen, len, "+paramStr+");\n" :
" double[] %TMP% = LibSpoofPrimitives.vect"+vectName+"Write(%IN1%, %POS1%, %LEN%, "+paramStr+");\n";
+ }
+ case VECT_IM2COL: {
+ String paramStr = getDnnParameterString(inputs, true);
+ return sparseGen ?
+ " double[] %TMP% = LibSpoofPrimitives.vectIm2colWrite(%IN1v%, %IN1i%, %POS1%, alen, len, "+paramStr+");\n" :
+ " double[] %TMP% = LibSpoofPrimitives.vectIm2colWrite(%IN1%, %POS1%, %LEN%, "+paramStr+");\n";
+ }
+ case VECT_CONV2DMM: {
+ return " double[] %TMP% = LibSpoofPrimitives.vectConv2dmmWrite(%IN2%, %IN1%, %POS2%, %POS1%, %LEN%, "
+ + getDnnParameterString(inputs, false) +");\n";
+ }
default:
throw new RuntimeException("Invalid nary type: "+this.toString());
}
}
public boolean isVectorPrimitive() {
- return this == VECT_CBIND || this == VECT_MAX_POOL || this == VECT_AVG_POOL;
+ return this == VECT_CBIND || this == VECT_MAX_POOL || this == VECT_AVG_POOL
+ || this == VECT_IM2COL || this == NaryType.VECT_CONV2DMM;
}
}
@@ -111,8 +125,11 @@ public class CNodeNary extends CNode
tmp = tmp.replace("%TMP%", var);
//replace sparse and dense inputs
- String varj = _inputs.get(0).getVarname();
- tmp = replaceUnaryPlaceholders(tmp, varj, false);
+ String varj1 = _inputs.get(0).getVarname();
+ String varj2 = _inputs.get(1).getVarname();
+ tmp = (_type == NaryType.VECT_CONV2DMM) ?
+ replaceBinaryPlaceholders(tmp, new String[]{varj1,varj2}, false) :
+ replaceUnaryPlaceholders(tmp, varj1, false);
sb.append(tmp);
@@ -128,6 +145,8 @@ public class CNodeNary extends CNode
case VECT_CBIND: return "n(cbind)";
case VECT_MAX_POOL: return "n(maxpool)";
case VECT_AVG_POOL: return "n(avgpool)";
+ case VECT_IM2COL: return "n(im2col)";
+ case VECT_CONV2DMM: return "n(conv2dmm)";
default:
return "m("+_type.name().toLowerCase()+")";
}
@@ -144,7 +163,7 @@ public class CNodeNary extends CNode
_dataType = DataType.MATRIX;
break;
case VECT_MAX_POOL:
- case VECT_AVG_POOL: //only stride 1, pad 0
+ case VECT_AVG_POOL: { //only stride 1, pad 0
int C = Integer.parseInt(_inputs.get(6).getVarname());
int H = Integer.parseInt(_inputs.get(7).getVarname());
int W = Integer.parseInt(_inputs.get(8).getVarname());
@@ -152,10 +171,28 @@ public class CNodeNary extends CNode
int S = Integer.parseInt(_inputs.get(12).getVarname());
long P = DnnUtils.getP(H, R, 1, 0);
long Q = DnnUtils.getQ(W, S, 1, 0);
- _rows = _inputs.get(0)._rows;
+ _rows = _inputs.get(0)._rows; //N
_cols = C * P * Q;
_dataType = DataType.MATRIX;
break;
+ }
+ case VECT_IM2COL:
+ _rows = 1;
+ _cols = -1;
+ _dataType = DataType.MATRIX;
+ break;
+ case VECT_CONV2DMM: {
+ int H = Integer.parseInt(_inputs.get(8).getVarname());
+ int W = Integer.parseInt(_inputs.get(9).getVarname());
+ int K = Integer.parseInt(_inputs.get(10).getVarname());
+ int R = Integer.parseInt(_inputs.get(12).getVarname());
+ int S = Integer.parseInt(_inputs.get(13).getVarname());
+ long P = DnnUtils.getP(H, R, 1, 0);
+ long Q = DnnUtils.getQ(W, S, 1, 0);
+ _rows = _inputs.get(0)._rows; //N
+ _cols = K * P * Q;
+ _dataType = DataType.MATRIX;
+ }
}
}
@@ -178,18 +215,46 @@ public class CNodeNary extends CNode
&& _type == that._type;
}
- private static String getPoolingParameterString(List<CNode> inputs) {
+ private static String getDnnParameterString(List<CNode> inputs, boolean unary) {
+ int off = unary ? 0 : 1;
+
//extract and derive individual parameters
- int C = Integer.parseInt(inputs.get(6).getVarname());
- int H = Integer.parseInt(inputs.get(7).getVarname());
- int W = Integer.parseInt(inputs.get(8).getVarname());
- int R = Integer.parseInt(inputs.get(11).getVarname());
- int S = Integer.parseInt(inputs.get(12).getVarname());
+ int C = Integer.parseInt(inputs.get(off+6).getVarname());
+ int H = Integer.parseInt(inputs.get(off+7).getVarname());
+ int W = Integer.parseInt(inputs.get(off+8).getVarname());
+ int K = Integer.parseInt(inputs.get(off+9).getVarname());
+ int R = Integer.parseInt(inputs.get(off+11).getVarname());
+ int S = Integer.parseInt(inputs.get(off+12).getVarname());
int P = (int) DnnUtils.getP(H, R, 1, 0);
int Q = (int) DnnUtils.getQ(W, S, 1, 0);
//construct parameter string
return "rix, " + StringUtils.join(
- new int[]{C, P, Q, R, S, H, W}, ',');
+ new int[]{C, P, Q, K, R, S, H, W}, ',');
+ }
+
+
+ private String replaceBinaryPlaceholders(String tmp, String[] vars, boolean vectIn) {
+ //replace sparse and dense inputs
+ for( int j=0; j<2; j++ ) {
+ String varj = vars[j];
+
+ //replace sparse and dense inputs
+ tmp = tmp.replace("%IN"+(j+1)+"v%", varj+"vals");
+ tmp = tmp.replace("%IN"+(j+1)+"i%", varj+"ix");
+ tmp = tmp.replace("%IN"+(j+1)+"%",
+ varj.startsWith("b") ? varj + ".values(rix)" : varj );
+
+ //replace start position of main input
+ tmp = tmp.replace("%POS"+(j+1)+"%", (_inputs.get(j) instanceof CNodeData
+ && _inputs.get(j).getDataType().isMatrix()) ? !varj.startsWith("b") ? varj+"i" :
+ (TemplateUtils.isMatrix(_inputs.get(j)) && _type!=NaryType.VECT_CONV2DMM) ? varj + ".pos(rix)" : "0" : "0");
+ }
+
+ //replace length
+ if( _inputs.get(0).getDataType().isMatrix() )
+ tmp = tmp.replace("%LEN%", _inputs.get(0).getVectorLength());
+
+ return tmp;
}
}
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/main/java/org/apache/sysml/hops/codegen/template/TemplateRow.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/hops/codegen/template/TemplateRow.java b/src/main/java/org/apache/sysml/hops/codegen/template/TemplateRow.java
index 9885909..8f7ea1a 100644
--- a/src/main/java/org/apache/sysml/hops/codegen/template/TemplateRow.java
+++ b/src/main/java/org/apache/sysml/hops/codegen/template/TemplateRow.java
@@ -116,8 +116,9 @@ public class TemplateRow extends TemplateBase
|| (HopRewriteUtils.isDnn(hop, OpOpDnn.BIASADD, OpOpDnn.BIASMULT)
&& hop.getInput().get(0).dimsKnown() && hop.getInput().get(1).dimsKnown()
&& hop.getInput().get(0).getDim2()>1)
- || (HopRewriteUtils.isDnn(hop, OpOpDnn.MAX_POOL, OpOpDnn.AVG_POOL)
- && hop.getInput().get(0).dimsKnown() && ((DnnOp)hop).isStride1Pad0());
+ || (HopRewriteUtils.isDnn(hop, OpOpDnn.MAX_POOL, OpOpDnn.AVG_POOL, OpOpDnn.CONV2D)
+ && hop.getInput().get(0).dimsKnown() && ((DnnOp)hop).isStride1Pad0()
+ && hop.getInput().get(1).dimsKnown()); //for conv2d
}
@Override
@@ -142,8 +143,9 @@ public class TemplateRow extends TemplateBase
|| (HopRewriteUtils.isDnn(hop, OpOpDnn.BIASADD, OpOpDnn.BIASMULT)
&& hop.getInput().get(0).dimsKnown() && hop.getInput().get(1).dimsKnown()
&& hop.getInput().get(0).getDim2()>1)
- || (HopRewriteUtils.isDnn(hop, OpOpDnn.MAX_POOL, OpOpDnn.AVG_POOL)
- && hop.getInput().get(0).dimsKnown() && ((DnnOp)hop).isStride1Pad0())
+ || (HopRewriteUtils.isDnn(hop, OpOpDnn.MAX_POOL, OpOpDnn.AVG_POOL, OpOpDnn.CONV2D)
+ && hop.getInput().get(0).dimsKnown() && ((DnnOp)hop).isStride1Pad0()
+ && hop.getInput().get(1).dimsKnown() && hop.getInput().get(1)!=input) //for conv2d
|| isPartOfValidCumAggChain(hop) //cum* with transpose
|| isPartOfValidTransposeMMChain(hop)); //t(f(X))%*%X
}
@@ -160,8 +162,9 @@ public class TemplateRow extends TemplateBase
|| (HopRewriteUtils.isDnn(hop, OpOpDnn.BIASADD, OpOpDnn.BIASMULT)
&& hop.getInput().get(0).dimsKnown() && hop.getInput().get(1).dimsKnown()
&& hop.getInput().get(0).getDim2()>1 )
- || (HopRewriteUtils.isDnn(hop, OpOpDnn.MAX_POOL, OpOpDnn.AVG_POOL)
- && hop.getInput().get(0).dimsKnown() && ((DnnOp)hop).isStride1Pad0())
+ || (HopRewriteUtils.isDnn(hop, OpOpDnn.MAX_POOL, OpOpDnn.AVG_POOL, OpOpDnn.CONV2D)
+ && hop.getInput().get(0).dimsKnown() && ((DnnOp)hop).isStride1Pad0()
+ && hop.getInput().get(1).dimsKnown() && hop.getInput().get(1)!=input) //for conv2d
|| (HopRewriteUtils.isDataGenOpWithLiteralInputs(input, DataGenMethod.SEQ)
&& HopRewriteUtils.hasOnlyUnaryBinaryParents(input, false))
|| (hop instanceof AggBinaryOp
@@ -488,6 +491,14 @@ public class TemplateRow extends TemplateBase
out = new CNodeNary(in, CNodeNary.NaryType
.valueOf("VECT_"+((DnnOp)hop).getOp().name()));
}
+ else if( HopRewriteUtils.isDnn(hop, OpOpDnn.CONV2D) ) {
+ CNode[] in1 = hop.getInput().stream().filter(h -> h!=hop.getInput().get(1))
+ .map(h ->tmp.get(h.getHopID())).toArray(CNode[]::new);
+ CNode im2col = new CNodeNary(in1, CNodeNary.NaryType.VECT_IM2COL);
+ CNode[] in2 = hop.getInput().stream().map(h -> (h==hop.getInput().get(0)) ?
+ im2col : tmp.get(h.getHopID())).toArray(CNode[]::new);
+ out = new CNodeNary(in2, CNodeNary.NaryType.VECT_CONV2DMM);
+ }
else if( hop instanceof NaryOp ) {
CNode[] inputs = new CNode[hop.getInput().size()];
for( int i=0; i<hop.getInput().size(); i++ ) {
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/main/java/org/apache/sysml/runtime/codegen/LibSpoofPrimitives.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/runtime/codegen/LibSpoofPrimitives.java b/src/main/java/org/apache/sysml/runtime/codegen/LibSpoofPrimitives.java
index c1460ce..e0c1c57 100644
--- a/src/main/java/org/apache/sysml/runtime/codegen/LibSpoofPrimitives.java
+++ b/src/main/java/org/apache/sysml/runtime/codegen/LibSpoofPrimitives.java
@@ -25,10 +25,12 @@ import org.apache.commons.math3.util.FastMath;
import org.apache.sysml.runtime.functionobjects.BitwAnd;
import org.apache.sysml.runtime.functionobjects.IntegerDivide;
import org.apache.sysml.runtime.functionobjects.Modulus;
+import org.apache.sysml.runtime.matrix.data.DenseBlockDRB;
import org.apache.sysml.runtime.matrix.data.LibMatrixDNN;
import org.apache.sysml.runtime.matrix.data.LibMatrixDNNPooling;
import org.apache.sysml.runtime.matrix.data.LibMatrixMult;
import org.apache.sysml.runtime.matrix.data.LibMatrixDNN.PoolingType;
+import org.apache.sysml.runtime.matrix.data.LibMatrixDNNIm2Col;
/**
* This library contains all vector primitives that are used in
@@ -2057,14 +2059,14 @@ public class LibSpoofPrimitives
//maxpool
- public static double[] vectMaxpoolWrite(double[] a, int ai, int len, int rix, int C, int P, int Q, int R, int S, int H, int W) {
+ public static double[] vectMaxpoolWrite(double[] a, int ai, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
double[] c = allocVector(C*P*Q, true);
LibMatrixDNNPooling.poolingDenseStride1Pad0(PoolingType.MAX,
-Double.MAX_VALUE, 1, a, c, rix, rix+1, ai, 0, C, P, Q, R, S, H, W);
return c;
}
- public static double[] vectMaxpoolWrite(double[] avals, int[] aix, int ai, int alen, int len, int rix, int C, int P, int Q, int R, int S, int H, int W) {
+ public static double[] vectMaxpoolWrite(double[] avals, int[] aix, int ai, int alen, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
double[] a = allocVector(len, true);
double[] c = allocVector(C*P*Q, true);
for(int k=ai; k<ai+alen; k++)
@@ -2076,14 +2078,14 @@ public class LibSpoofPrimitives
//avgpool
- public static double[] vectAvgpoolWrite(double[] a, int ai, int len, int rix, int C, int P, int Q, int R, int S, int H, int W) {
+ public static double[] vectAvgpoolWrite(double[] a, int ai, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
double[] c = allocVector(C*P*Q, true);
LibMatrixDNNPooling.poolingDenseStride1Pad0(PoolingType.AVG,
0, 1/(R*S), a, c, rix, rix+1, ai, 0, C, P, Q, R, S, H, W);
return c;
}
- public static double[] vectAvgpoolWrite(double[] avals, int[] aix, int ai, int alen, int len, int rix, int C, int P, int Q, int R, int S, int H, int W) {
+ public static double[] vectAvgpoolWrite(double[] avals, int[] aix, int ai, int alen, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
double[] a = allocVector(len, true);
double[] c = allocVector(C*P*Q, true);
for(int k=ai; k<ai+alen; k++)
@@ -2093,6 +2095,34 @@ public class LibSpoofPrimitives
return c;
}
+ //im2col
+
+ public static double[] vectIm2colWrite(double[] a, int ai, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
+ double[] c = allocVector(C*R*S * P*Q, true);
+ LibMatrixDNNIm2Col.im2colDenseStride1Pad0(a, c, ai, C, R, S, H, W, P, Q);
+ return c;
+ }
+
+ public static double[] vectIm2colWrite(double[] avals, int[] aix, int ai, int alen, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
+ double[] a = allocVector(len, true);
+ double[] c = allocVector(C*R*S * P*Q, true);
+ for(int k=ai; k<ai+alen; k++)
+ a[aix[k]] = avals[k];
+ LibMatrixDNNIm2Col.im2colDenseStride1Pad0(a, c, ai, C, R, S, H, W, P, Q);
+ return c;
+ }
+
+ //conv2d matrix mult
+
+ public static double[] vectConv2dmmWrite(double[] a, double[] b, int ai, int bi, int len, int rix, int C, int P, int Q, int K, int R, int S, int H, int W) {
+ double[] c = allocVector(K*P*Q, true);
+ int CRS = C*R*S, PQ = P*Q;
+ LibMatrixMult.matrixMultDenseDenseMM(
+ new DenseBlockDRB(a, K, CRS), new DenseBlockDRB(b, CRS, PQ),
+ new DenseBlockDRB(c, K, PQ), PQ, CRS, 0, K, 0, PQ);
+ return c;
+ }
+
//complex builtin functions that are not directly generated
//(included here in order to reduce the number of imports)
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixDNNIm2Col.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixDNNIm2Col.java b/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixDNNIm2Col.java
index d344c93..dd2473e 100644
--- a/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixDNNIm2Col.java
+++ b/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixDNNIm2Col.java
@@ -41,7 +41,7 @@ public class LibMatrixDNNIm2Col
//dense and sparse operation dispatch
if( !in.sparse && stride1Pad0 && !trans )
im2colDenseStride1Pad0(in.getDenseBlockValues(),
- out.getDenseBlockValues(), r, C, R, S, H, W, P, Q);
+ out.getDenseBlockValues(), r*C*H*W, C, R, S, H, W, P, Q);
else if( !in.sparse )
im2colDense(in.getDenseBlockValues(), out.getDenseBlockValues(),
r, C, R, S, H, W, P, Q, stride_h, stride_w, pad_h, pad_w, trans);
@@ -50,8 +50,7 @@ public class LibMatrixDNNIm2Col
stride_h, stride_w, pad_h, pad_w, trans);
}
- public static void im2colDenseStride1Pad0(double[] in, double[] out, int r, int C, int R, int S, int H, int W, int P, int Q) {
- int nOffset = r * C * H * W;
+ public static void im2colDenseStride1Pad0(double[] in, double[] out, int ai, int C, int R, int S, int H, int W, int P, int Q) {
int CRS = C * R * S;
for (int c = 0; c < CRS; ++c) {
int wOffset = c % S;
@@ -60,7 +59,7 @@ public class LibMatrixDNNIm2Col
for (int h = 0; h < P; ++h) {
int hPadded = h + hOffset;
int outOffset = (c * P + h) * Q;
- int inputOffset = nOffset + (cInput * H + hPadded) * W;
+ int inputOffset = ai + (cInput * H + hPadded) * W;
System.arraycopy(in, inputOffset + wOffset, out, outOffset, Q);
int w = Q - 1;
int wPadded = w + wOffset;
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixMult.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixMult.java b/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixMult.java
index 8f60003..ad3e3b2 100644
--- a/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixMult.java
+++ b/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixMult.java
@@ -1046,9 +1046,10 @@ public class LibMatrixMult
}
}
- private static void matrixMultDenseDenseMM(DenseBlock a, DenseBlock b, DenseBlock c, int n, int cd, int rl, int ru, int cl, int cu) {
+ //note: public for use by codegen for consistency
+ public static void matrixMultDenseDenseMM(DenseBlock a, DenseBlock b, DenseBlock c, int n, int cd, int rl, int ru, int cl, int cu) {
//1) Unrolled inner loop (for better instruction-level parallelism)
- //2) Blocked execution (for less cache trashing in parallel exec)
+ //2) Blocked execution (for less cache trashing in parallel exec)
//3) Asymmetric block sizes (for less misses in inner loop, yet blocks in L1/L2)
final int blocksizeI = 32; //64//256KB c block (typical L2 size per core), 32KB a block
@@ -3093,7 +3094,7 @@ public class LibMatrixMult
{
double val = 0;
final int bn = len%8;
-
+
//compute rest
for( int i = 0; i < bn; i++, ai++, bi++ )
val += a[ ai ] * b[ bi ];
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowAggTmplTest.java
----------------------------------------------------------------------
diff --git a/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowAggTmplTest.java b/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowAggTmplTest.java
index d0a417d..2360092 100644
--- a/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowAggTmplTest.java
+++ b/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowAggTmplTest.java
@@ -82,6 +82,7 @@ public class RowAggTmplTest extends AutomatedTestBase
private static final String TEST_NAME43 = TEST_NAME+"43"; //bias_add(X,B) + bias_mult(X,B)
private static final String TEST_NAME44 = TEST_NAME+"44"; //maxpool(X - mean(X)) + 7;
private static final String TEST_NAME45 = TEST_NAME+"45"; //vector allocation;
+ private static final String TEST_NAME46 = TEST_NAME+"46"; //conv2d(X - mean(X), F1) + conv2d(X - mean(X), F2);
private static final String TEST_DIR = "functions/codegen/";
private static final String TEST_CLASS_DIR = TEST_DIR + RowAggTmplTest.class.getSimpleName() + "/";
@@ -93,7 +94,7 @@ public class RowAggTmplTest extends AutomatedTestBase
@Override
public void setUp() {
TestUtils.clearAssertionInformation();
- for(int i=1; i<=45; i++)
+ for(int i=1; i<=46; i++)
addTestConfiguration( TEST_NAME+i, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME+i, new String[] { String.valueOf(i) }) );
}
@@ -771,6 +772,21 @@ public class RowAggTmplTest extends AutomatedTestBase
public void testCodegenRowAgg45SP() {
testCodegenIntegration( TEST_NAME45, false, ExecType.SPARK );
}
+
+ @Test
+ public void testCodegenRowAggRewrite46CP() {
+ testCodegenIntegration( TEST_NAME46, true, ExecType.CP );
+ }
+
+ @Test
+ public void testCodegenRowAgg46CP() {
+ testCodegenIntegration( TEST_NAME46, false, ExecType.CP );
+ }
+
+ @Test
+ public void testCodegenRowAgg46SP() {
+ testCodegenIntegration( TEST_NAME46, false, ExecType.SPARK );
+ }
private void testCodegenIntegration( String testname, boolean rewrites, ExecType instType )
{
@@ -793,17 +809,17 @@ public class RowAggTmplTest extends AutomatedTestBase
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + testname + ".dml";
- programArgs = new String[]{"-explain", "recompile_runtime", "-stats", "-args", output("S") };
+ programArgs = new String[]{"-explain", "-stats", "-args", output("S") };
fullRScriptName = HOME + testname + ".R";
rCmd = getRCmd(inputDir(), expectedDir());
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;
- runTest(true, false, null, -1);
- runRScript(true);
+ runTest(true, false, null, -1);
+ runRScript(true);
- //compare matrices
+ //compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("S");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("S");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
@@ -836,6 +852,9 @@ public class RowAggTmplTest extends AutomatedTestBase
if( testname.equals(TEST_NAME44) )
Assert.assertTrue(!heavyHittersContainsSubString("maxpooling")
&& !heavyHittersContainsSubString("spoof", 2));
+ if( testname.equals(TEST_NAME46) )
+ Assert.assertTrue(!heavyHittersContainsSubString("conv2d")
+ && !heavyHittersContainsSubString("spoof", 2));
}
finally {
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowConv2DOperationsTest.java
----------------------------------------------------------------------
diff --git a/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowConv2DOperationsTest.java b/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowConv2DOperationsTest.java
index 6910c03..46e10a3 100644
--- a/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowConv2DOperationsTest.java
+++ b/src/test/java/org/apache/sysml/test/integration/functions/codegen/RowConv2DOperationsTest.java
@@ -29,6 +29,7 @@ import org.apache.sysml.runtime.matrix.data.MatrixValue.CellIndex;
import org.apache.sysml.test.integration.AutomatedTestBase;
import org.apache.sysml.test.integration.TestConfiguration;
import org.apache.sysml.test.utils.TestUtils;
+import org.junit.Assert;
import org.junit.Test;
public class RowConv2DOperationsTest extends AutomatedTestBase
@@ -111,8 +112,8 @@ public class RowConv2DOperationsTest extends AutomatedTestBase
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("B");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("B");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
- //Assert.assertTrue(heavyHittersContainsSubString("spoofRA")
- // || heavyHittersContainsSubString("sp_spoofRA"));
+ Assert.assertTrue(heavyHittersContainsSubString("spoofRA")
+ || heavyHittersContainsSubString("sp_spoofRA"));
}
finally {
rtplatform = platformOld;
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/test/scripts/functions/codegen/rowAggPattern46.R
----------------------------------------------------------------------
diff --git a/src/test/scripts/functions/codegen/rowAggPattern46.R b/src/test/scripts/functions/codegen/rowAggPattern46.R
new file mode 100644
index 0000000..e40ebaa
--- /dev/null
+++ b/src/test/scripts/functions/codegen/rowAggPattern46.R
@@ -0,0 +1,107 @@
+#-------------------------------------------------------------
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+#-------------------------------------------------------------
+args <- commandArgs(TRUE)
+library("Matrix")
+library("matrixStats")
+
+pad_image <- function(img, Hin, Win, padh, padw){
+ C = nrow(img)
+ img_padded = matrix(0, C, (Hin+2*padh)*(Win+2*padw), byrow=TRUE) # zeros
+ for (c in 1:C) {
+ img_slice = matrix(img[c,], Hin, Win, byrow=TRUE) # depth slice C reshaped
+ img_padded_slice = matrix(0, Hin+2*padh, Win+2*padw)
+ img_padded_slice[(padh+1):(padh+Hin), (padw+1):(padw+Win)] = img_slice
+ img_padded[c,] = matrix(t(img_padded_slice), 1, (Hin+2*padh)*(Win+2*padw)) # reshape
+ }
+ img_padded
+}
+
+im2col <- function(img, Hin, Win, Hf, Wf, strideh, stridew) {
+ C = nrow(img)
+ Hout = as.integer((Hin - Hf) / strideh + 1)
+ Wout = as.integer((Win - Wf) / stridew + 1)
+
+ img_cols = matrix(0, C*Hf*Wf, Hout*Wout, byrow=TRUE) # zeros
+ for (hout in 1:Hout) { # all output rows
+ hin = (hout-1) * strideh + 1
+ for (wout in 1:Wout) { # all output columns
+ win = (wout-1) * stridew + 1
+ # Extract a local patch of the input image corresponding spatially to the filter sizes.
+ img_patch = matrix(0, C, Hf*Wf, byrow=TRUE) # zeros
+ for (c in 1:C) { # all channels
+ img_slice = matrix(img[c,], Hin, Win, byrow=TRUE) # reshape
+ img_patch[c,] = matrix(t(img_slice[hin:(hin+Hf-1), win:(win+Wf-1)]), 1, Hf*Wf)
+ }
+ img_cols[,(hout-1)*Wout + wout] = matrix(t(img_patch), C*Hf*Wf, 1) # reshape
+ }
+ }
+ img_cols
+}
+
+conv2d <- function(X, W, C, Hin, Win, Hf, Wf, strideh, stridew, padh, padw) {
+ N = nrow(X)
+ F = nrow(W)
+ Hout = as.integer((Hin + 2 * padh - Hf) / strideh + 1)
+ Wout = as.integer((Win + 2 * padw - Wf) / stridew + 1)
+
+ # Create output volume
+ out = matrix(0, N, F*Hout*Wout, byrow=TRUE)
+
+ # Convolution - im2col implementation
+ for (n in 1:N) { # all examples
+ Xn = matrix(X[n,], C, Hin*Win, byrow=TRUE) # reshape
+
+ # Pad image
+ Xn_padded = pad_image(Xn, Hin, Win, padh, padw) # shape (C, (Hin+2*padh)*(Win+2*padw))
+
+ # Extract local image patches into columns with im2col, of shape (C*Hf*Wf, Hout*Wout)
+ Xn_padded_cols = im2col(Xn_padded, Hin+2*padh, Win+2*padw, Hf, Wf, strideh, stridew)
+
+ # Convolve patches with filters
+ outn = W %*% Xn_padded_cols # shape (F, Hout*Wout)
+ out[n,] = matrix(t(outn), 1, F*Hout*Wout) # reshape
+ }
+
+ out
+}
+
+imgSize=8
+numImg=16
+numChannels=4
+numFilters=3
+filterSize=4
+stride=1
+pad=0
+
+Hout = as.integer((imgSize + 2 * pad - filterSize) / stride + 1)
+
+X = matrix(seq(1, numImg*numChannels*imgSize*imgSize), numImg, numChannels*imgSize*imgSize, byrow=TRUE);
+W1 = matrix(seq(1, numFilters*numChannels*filterSize*filterSize), numFilters, numChannels*filterSize*filterSize, byrow=TRUE)
+W2 = matrix(seq(1, numFilters*numChannels*filterSize*filterSize)+7, numFilters, numChannels*filterSize*filterSize, byrow=TRUE)
+b = matrix(seq(1, numFilters), numFilters, 1, byrow=TRUE)
+
+X = X - rowMeans(X)
+
+R1 = conv2d(X, W1, numChannels, imgSize, imgSize, filterSize, filterSize, stride, stride, pad, pad);
+R2 = conv2d(X, W2, numChannels, imgSize, imgSize, filterSize, filterSize, stride, stride, pad, pad);
+R = R1 + R2;
+
+writeMM(as(R,"CsparseMatrix"), paste(args[2], "S", sep=""))
http://git-wip-us.apache.org/repos/asf/systemml/blob/fce9d978/src/test/scripts/functions/codegen/rowAggPattern46.dml
----------------------------------------------------------------------
diff --git a/src/test/scripts/functions/codegen/rowAggPattern46.dml b/src/test/scripts/functions/codegen/rowAggPattern46.dml
new file mode 100644
index 0000000..745ff2f
--- /dev/null
+++ b/src/test/scripts/functions/codegen/rowAggPattern46.dml
@@ -0,0 +1,43 @@
+#-------------------------------------------------------------
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+#-------------------------------------------------------------
+
+imgSize=8
+numImg=16
+numChannels=4
+numFilters=3
+filterSize=4
+stride=1
+pad=0
+
+X = matrix(seq(1, numImg*numChannels*imgSize*imgSize), rows=numImg, cols=numChannels*imgSize*imgSize);
+W1 = matrix(seq(1, numFilters*numChannels*filterSize*filterSize), rows=numFilters, cols=numChannels*filterSize*filterSize)
+W2 = matrix(seq(1, numFilters*numChannels*filterSize*filterSize)+7, rows=numFilters, cols=numChannels*filterSize*filterSize)
+b = matrix(seq(1, numFilters), rows=numFilters, cols=1)
+
+while(FALSE){}
+
+X = X - rowMeans(X);
+
+R1 = conv2d(X, W1, padding=[pad, pad], stride=[stride, stride], input_shape=[numImg, numChannels, imgSize, imgSize], filter_shape=[numFilters, numChannels, filterSize, filterSize])
+R2 = conv2d(X, W2, padding=[pad, pad], stride=[stride, stride], input_shape=[numImg, numChannels, imgSize, imgSize], filter_shape=[numFilters, numChannels, filterSize, filterSize])
+R = R1 + R2;
+
+write(R, $1, format="text");