parallelize collections

README.md

@@ -23,7 +23,7 @@ The tool uses the following terminology:
 - _Matrix factor_ referring to the sub-elements of a slice. (Internally, type `Array[Array[Double]]`)
 - _Factor_ (or _matrix factor element_) referring to the individual elements of a matrix factor. (Internally, type `Array[Array[Double]]`)
 
-Beware that factors are assumed to be represented by a limited number of bits. Unless the factors are passed to the tool manually, it assumes a slightly asymmetric distribution around zero. Moreover, the current algorithm for picking factors for slice rows suffers from exponential runtime in the number of non-zero elements. This means the overall tool runs rather slowly, even for relatively small matrices. We provide automated test flows for matrix sizes up to $256\times256$, which can execute in a few minutes on a laptop.
+Beware that factors are assumed to be represented by a limited number of bits. Unless the factors are passed to the tool manually, it assumes a slightly asymmetric distribution around zero. Moreover, the current algorithm for picking factors for slice rows suffers from exponential runtime in the number of non-zero elements. This means the overall tool runs rather slowly, even for relatively small matrices. We provide automated test flows for matrix sizes up to $32\times32$, which can execute in a few minutes on a laptop.
 
 ***
 # Requirements

build.sbt

@@ -11,7 +11,8 @@ lazy val root = (project in file("."))
     name := "CMVM",
     libraryDependencies ++= Seq(
       "edu.berkeley.cs" %% "chisel3" % chiselVersion,
-      "edu.berkeley.cs" %% "chiseltest" % "0.5.4" % "test"
+      "edu.berkeley.cs" %% "chiseltest" % "0.5.4" % "test",
+      "org.scala-lang.modules" %% "scala-parallel-collections" % "1.0.4"
     ),
     scalacOptions ++= Seq(
       "-language:reflectiveCalls",