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Posted to commits@systemml.apache.org by ni...@apache.org on 2018/10/09 20:57:38 UTC
systemml git commit: [SYSTEMML-445] Extend coverage for GPU batchnorm
test rewrite
Repository: systemml
Updated Branches:
refs/heads/master fab31fd1f -> 512fb9e11
[SYSTEMML-445] Extend coverage for GPU batchnorm test rewrite
- If inv_var rewrite has already been applied, the application of GPU
batchnorm test rewrite (and CuDNN batchnorm kernel) is skipped. This
commit fixes this performance regression.
- Also, this commit allows for forcing of GPU rewrites in case of forced
GPU mode.
Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/512fb9e1
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/512fb9e1
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/512fb9e1
Branch: refs/heads/master
Commit: 512fb9e119541ae9d7dae58c0812a89d569d1ca0
Parents: fab31fd
Author: Niketan Pansare <np...@us.ibm.com>
Authored: Tue Oct 9 13:56:47 2018 -0700
Committer: Niketan Pansare <np...@us.ibm.com>
Committed: Tue Oct 9 13:56:47 2018 -0700
----------------------------------------------------------------------
.../sysml/hops/rewrite/HopDagPatternMatcher.java | 15 +++++++++++++++
.../sysml/hops/rewrite/RewriteGPUSpecificOps.java | 2 +-
2 files changed, 16 insertions(+), 1 deletion(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/systemml/blob/512fb9e1/src/main/java/org/apache/sysml/hops/rewrite/HopDagPatternMatcher.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/hops/rewrite/HopDagPatternMatcher.java b/src/main/java/org/apache/sysml/hops/rewrite/HopDagPatternMatcher.java
index 51b1812..33cd5ed 100644
--- a/src/main/java/org/apache/sysml/hops/rewrite/HopDagPatternMatcher.java
+++ b/src/main/java/org/apache/sysml/hops/rewrite/HopDagPatternMatcher.java
@@ -294,6 +294,19 @@ public class HopDagPatternMatcher {
return new HopDagPatternMatcher().addPredicate("sqrt", h -> HopRewriteUtils.isUnary(h, OpOp1.SQRT))
.addChildMatcher(child);
}
+ public static HopDagPatternMatcher inv_var(HopDagPatternMatcher var, HopDagPatternMatcher eps) {
+ return new HopDagPatternMatcher().addPredicate("sqrt", h -> {
+ if(HopRewriteUtils.isDnn(h, OpOpDnn.INV_VAR)) {
+ return true;
+ }
+ else {
+ return HopRewriteUtils.isBinary(h, OpOp2.DIV) && HopRewriteUtils.isLiteralOfValue(h.getInput().get(0), 1.0) &&
+ HopRewriteUtils.isUnary(h.getInput().get(1), OpOp1.SQRT) &&
+ HopRewriteUtils.isBinary(h.getInput().get(1).getInput().get(0), OpOp2.PLUS);
+ }
+ })
+ .addChildMatcher(var, eps);
+ }
public static HopDagPatternMatcher div(HopDagPatternMatcher child1, HopDagPatternMatcher child2) {
return new HopDagPatternMatcher().addPredicate("div", h -> HopRewriteUtils.isBinary(h, OpOp2.DIV))
.addChildMatcher(child1, child2);
@@ -370,6 +383,8 @@ public class HopDagPatternMatcher {
.addChildMatcher(child1, dummy);
}
private static boolean _fitsOnGPU(Hop h, double multiplier) {
+ if(ConfigurationManager.isForcedGPU())
+ return true;
double memEst = multiplier*h.getMemEstimate();
return ConfigurationManager.isGPU() && h.dimsKnown() && OptimizerUtils.isMemoryBasedOptLevel() &&
memEst < OptimizerUtils.getLocalMemBudget() && memEst < GPUContextPool.initialGPUMemBudget();
http://git-wip-us.apache.org/repos/asf/systemml/blob/512fb9e1/src/main/java/org/apache/sysml/hops/rewrite/RewriteGPUSpecificOps.java
----------------------------------------------------------------------
diff --git a/src/main/java/org/apache/sysml/hops/rewrite/RewriteGPUSpecificOps.java b/src/main/java/org/apache/sysml/hops/rewrite/RewriteGPUSpecificOps.java
index 53d368b..577adc3 100644
--- a/src/main/java/org/apache/sysml/hops/rewrite/RewriteGPUSpecificOps.java
+++ b/src/main/java/org/apache/sysml/hops/rewrite/RewriteGPUSpecificOps.java
@@ -178,7 +178,7 @@ public class RewriteGPUSpecificOps extends HopRewriteRuleWithPatternMatcher {
HopDagPatternMatcher norm =
bias_multiply(
bias_add(leaf("X", MATRIX), unaryMinus(leaf("mean", MATRIX))), // bias_add(X, -mean)
- div(1, sqrt(plus(leaf("var", MATRIX), leaf("eps", SCALAR))))); // 1/sqrt(var+eps)
+ inv_var(leaf("var", MATRIX), leaf("eps", SCALAR))); // 1/sqrt(var+eps)
// hi = bias_add(bias_multiply(norm, gamma), beta)
_batchNormTest =
bias_add(