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Many tools and utilities are present in spinal.lib but some are already present in the SpinalHDL Core.




widthOf(x : BitVector)


Return the width of a Bits/UInt/SInt signal

log2Up(x : BigInt)


Return the number of bits needed to represent x states

isPow2(x : BigInt)


Return true if x is a power of two

roundUp(that : BigInt, by : BigInt)


Return the first by multiply from that (included)

Cat(x: Data*)


Concatenate all arguments, from MSB to LSB, see Cat

Cat(x: Iterable[Data])


Conactenate arguments, from LSB to MSB, see Cat


As listed above, there are two version of Cat. Both versions concatenate the signals they contain, with a subtle difference:

  • Cat(x: Data*) takes an arbitrary number of hardware signals as parameters. It mimics other HDLs and the leftmost parameter becomes the MSB of the resulting Bits, the rightmost the LSB side. Said differently: the input is concatenated in the order as written.

  • Cat(x: Iterable[Data]) which takes a single Scala iterable collection (Seq / Set / List / …) containing hardware signals. This version places the first element of the list into the LSB, and the last into the MSB.

This seeming difference comes mostly from the convention that Bits are written from the hightest index to the lowest index, while Lists are written down starting from index 0 to the highest index. Cat places index 0 of both conventions at the LSB.

val bit0, bit1, bit2 = Bool()

val first = Cat(bit2, bit1, bit0)

// is equivalent to

val signals = List(bit0, bit1, bit2)
val second = Cat(signals)

Cloning hardware datatypes

You can clone a given hardware data type by using the cloneOf(x) function. It will return a new instance of the same Scala type and parameters.

For example:

def plusOne(value : UInt) : UInt = {
  // Will provide new instance of a UInt with the same width as ``value``
  val temp = cloneOf(value)
  temp := value + 1
  return temp

// treePlusOne will become a 8 bits value
val treePlusOne = plusOne(U(3, 8 bits))

You can get more information about how hardware data types are managed on the Hardware types page.


If you use the cloneOf function on a Bundle, this Bundle should be a case class or should override the clone function internally.

// An example of a regular 'class' with 'override def clone()' function
class MyBundle(ppp : Int) extends Bundle {
   val a = UInt(ppp bits)
   override def clone = new MyBundle(ppp)
 val x = new MyBundle(3)
 val typeDef = HardType(new MyBundle(3))
 val y = typeDef()

 cloneOf(x) // Need clone method, else it errors
 cloneOf(y) // Is ok

Passing a datatype as construction parameter

Many pieces of reusable hardware need to be parameterized by some data type. For example if you want to define a FIFO or a shift register, you need a parameter to specify which kind of payload you want for the component.

There are two similar ways to do this.

The old way

A good example of the old way to do this is in this definition of a ShiftRegister component:

case class ShiftRegister[T <: Data](dataType: T, depth: Int) extends Component {
  val io = new Bundle {
    val input  = in (cloneOf(dataType))
    val output = out(cloneOf(dataType))
  // ...

And here is how you can instantiate the component:

val shiftReg = ShiftRegister(Bits(32 bits), depth = 8)

As you can see, the raw hardware type is directly passed as a construction parameter. Then each time you want to create an new instance of that kind of hardware data type, you need to use the cloneOf(...) function. Doing things this way is not super safe as it’s easy to forget to use cloneOf.

The safe way

An example of the safe way to pass a data type parameter is as follows:

case class ShiftRegister[T <: Data](dataType: HardType[T], depth: Int) extends Component {
  val io = new Bundle {
    val input  = in (dataType())
    val output = out(dataType())
  // ...

And here is how you instantiate the component (exactly the same as before):

val shiftReg = ShiftRegister(Bits(32 bits), depth = 8)

Notice how the example above uses a HardType wrapper around the raw data type T, which is a “blueprint” definition of a hardware data type. This way of doing things is easier to use than the “old way”, because to create a new instance of the hardware data type you only need to call the apply function of that HardType (or in other words, just add parentheses after the parameter).

Additionally, this mechanism is completely transparent from the point of view of the user, as a hardware data type can be implicitly converted into a HardType.

Frequency and time

SpinalHDL has a dedicated syntax to define frequency and time values:

val frequency = 100 MHz      // infers type TimeNumber
val timeoutLimit = 3 ms      // infers type HertzNumber
val period = 100 us          // infers type TimeNumber

val periodCycles = frequency * period             // infers type BigDecimal
val timeoutCycles = frequency * timeoutLimit      // infers type BigDecimal
For time definitions you can use following postfixes to get a TimeNumber:
fs, ps, ns, us, ms, sec, mn, hr
For time definitions you can use following postfixes to get a HertzNumber:
Hz, KHz, MHz, GHz, THz

TimeNumber and HertzNumber are based on the PhysicalNumber class which use scala BigDecimal to store numbers.

Binary prefix

SpinalHDL allows the definition of integer numbers using binary prefix notation according to IEC.

val memSize = 512 MiB      // infers type BigInt
val dpRamSize = 4 KiB      // infers type BigInt

The following binary prefix notations are available:

Binary Prefix


Byte, Bytes



1024 == 1 << 10


10242 == 1 << 20


10243 == 1 << 30


10244 == 1 << 40


10245 == 1 << 50


10246 == 1 << 60


10247 == 1 << 70


10248 == 1 << 80

Of course, BigInt can also be printed as a string in bytes unit. BigInt(1024).byteUnit.

val memSize = 512 MiB

>> 536870912

>> 512MiB

val dpRamSize = BigInt("123456789", 16)

>> 4GiB+564MiB+345KiB+905Byte

println((32.MiB + 12.KiB + 223).byteUnit())
>> 32MiB+12KiB+223Byte

println((32.MiB + 12.KiB + 223).byteUnit(ceil = true))
>> 33~MiB