tests: Trim .nim files trailing whitespace
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@ -1,168 +1,168 @@
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discard """
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outputsub: "Success!"
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"""
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# This is adapted from a benchmark written by John Ellis and Pete Kovac
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# of Post Communications.
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# It was modified by Hans Boehm of Silicon Graphics.
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#
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# This is no substitute for real applications. No actual application
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# is likely to behave in exactly this way. However, this benchmark was
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# designed to be more representative of real applications than other
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# Java GC benchmarks of which we are aware.
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# It attempts to model those properties of allocation requests that
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# are important to current GC techniques.
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# It is designed to be used either to obtain a single overall performance
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# number, or to give a more detailed estimate of how collector
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# performance varies with object lifetimes. It prints the time
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# required to allocate and collect balanced binary trees of various
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# sizes. Smaller trees result in shorter object lifetimes. Each cycle
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# allocates roughly the same amount of memory.
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# Two data structures are kept around during the entire process, so
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# that the measured performance is representative of applications
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# that maintain some live in-memory data. One of these is a tree
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# containing many pointers. The other is a large array containing
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# double precision floating point numbers. Both should be of comparable
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# size.
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#
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# The results are only really meaningful together with a specification
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# of how much memory was used. It is possible to trade memory for
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# better time performance. This benchmark should be run in a 32 MB
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# heap, though we don't currently know how to enforce that uniformly.
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#
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# Unlike the original Ellis and Kovac benchmark, we do not attempt
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# measure pause times. This facility should eventually be added back
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# in. There are several reasons for omitting it for now. The original
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# implementation depended on assumptions about the thread scheduler
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# that don't hold uniformly. The results really measure both the
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# scheduler and GC. Pause time measurements tend to not fit well with
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# current benchmark suites. As far as we know, none of the current
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# commercial Java implementations seriously attempt to minimize GC pause
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# times.
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#
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# Known deficiencies:
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# - No way to check on memory use
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# - No cyclic data structures
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# - No attempt to measure variation with object size
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# - Results are sensitive to locking cost, but we dont
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# check for proper locking
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#
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import
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strutils, times
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type
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PNode = ref TNode
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TNode {.final.} = object
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left, right: PNode
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i, j: int
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proc newNode(L, r: PNode): PNode =
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new(result)
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result.left = L
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result.right = r
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const
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kStretchTreeDepth = 18 # about 16Mb
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kLongLivedTreeDepth = 16 # about 4Mb
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kArraySize = 500000 # about 4Mb
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kMinTreeDepth = 4
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kMaxTreeDepth = 16
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# Nodes used by a tree of a given size
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proc TreeSize(i: int): int = return ((1 shl (i + 1)) - 1)
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# Number of iterations to use for a given tree depth
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proc NumIters(i: int): int =
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return 2 * TreeSize(kStretchTreeDepth) div TreeSize(i)
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# Build tree top down, assigning to older objects.
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proc Populate(iDepth: int, thisNode: PNode) =
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if iDepth <= 0:
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return
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else:
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new(thisNode.left)
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new(thisNode.right)
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Populate(iDepth-1, thisNode.left)
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Populate(iDepth-1, thisNode.right)
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# Build tree bottom-up
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proc MakeTree(iDepth: int): PNode =
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if iDepth <= 0:
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new(result)
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else:
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return newNode(MakeTree(iDepth-1), MakeTree(iDepth-1))
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proc PrintDiagnostics() =
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echo("Total memory available: " & $getTotalMem() & " bytes")
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echo("Free memory: " & $getFreeMem() & " bytes")
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proc TimeConstruction(depth: int) =
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var
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root, tempTree: PNode
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iNumIters: int
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iNumIters = NumIters(depth)
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echo("Creating " & $iNumIters & " trees of depth " & $depth)
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var t = epochTime()
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for i in 0..iNumIters-1:
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new(tempTree)
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Populate(depth, tempTree)
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tempTree = nil
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echo("\tTop down construction took " & $(epochTime() - t) & "msecs")
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t = epochTime()
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for i in 0..iNumIters-1:
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tempTree = MakeTree(depth)
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tempTree = nil
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echo("\tBottom up construction took " & $(epochTime() - t) & "msecs")
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type
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tMyArray = seq[float]
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proc main() =
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var
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root, longLivedTree, tempTree: PNode
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myarray: tMyArray
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echo("Garbage Collector Test")
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echo(" Stretching memory with a binary tree of depth " & $kStretchTreeDepth)
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PrintDiagnostics()
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var t = epochTime()
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# Stretch the memory space quickly
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tempTree = MakeTree(kStretchTreeDepth)
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tempTree = nil
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# Create a long lived object
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echo(" Creating a long-lived binary tree of depth " &
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$kLongLivedTreeDepth)
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new(longLivedTree)
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Populate(kLongLivedTreeDepth, longLivedTree)
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# Create long-lived array, filling half of it
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echo(" Creating a long-lived array of " & $kArraySize & " doubles")
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newSeq(myarray, kArraySize)
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for i in 0..kArraySize div 2 -1:
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myarray[i] = 1.0 / toFloat(i)
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PrintDiagnostics()
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var d = kMinTreeDepth
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while d <= kMaxTreeDepth:
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TimeConstruction(d)
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inc(d, 2)
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if longLivedTree == nil or myarray[1000] != 1.0/1000.0:
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echo("Failed")
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# fake reference to LongLivedTree
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# and array to keep them from being optimized away
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var elapsed = epochTime() - t
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PrintDiagnostics()
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echo("Completed in " & $elapsed & "ms. Success!")
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discard """
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outputsub: "Success!"
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"""
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# This is adapted from a benchmark written by John Ellis and Pete Kovac
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# of Post Communications.
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# It was modified by Hans Boehm of Silicon Graphics.
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#
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# This is no substitute for real applications. No actual application
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# is likely to behave in exactly this way. However, this benchmark was
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# designed to be more representative of real applications than other
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# Java GC benchmarks of which we are aware.
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# It attempts to model those properties of allocation requests that
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# are important to current GC techniques.
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# It is designed to be used either to obtain a single overall performance
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# number, or to give a more detailed estimate of how collector
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# performance varies with object lifetimes. It prints the time
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# required to allocate and collect balanced binary trees of various
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# sizes. Smaller trees result in shorter object lifetimes. Each cycle
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# allocates roughly the same amount of memory.
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# Two data structures are kept around during the entire process, so
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# that the measured performance is representative of applications
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# that maintain some live in-memory data. One of these is a tree
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# containing many pointers. The other is a large array containing
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# double precision floating point numbers. Both should be of comparable
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# size.
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#
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# The results are only really meaningful together with a specification
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# of how much memory was used. It is possible to trade memory for
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# better time performance. This benchmark should be run in a 32 MB
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# heap, though we don't currently know how to enforce that uniformly.
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#
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# Unlike the original Ellis and Kovac benchmark, we do not attempt
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# measure pause times. This facility should eventually be added back
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# in. There are several reasons for omitting it for now. The original
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# implementation depended on assumptions about the thread scheduler
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# that don't hold uniformly. The results really measure both the
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# scheduler and GC. Pause time measurements tend to not fit well with
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# current benchmark suites. As far as we know, none of the current
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# commercial Java implementations seriously attempt to minimize GC pause
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# times.
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#
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# Known deficiencies:
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# - No way to check on memory use
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# - No cyclic data structures
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# - No attempt to measure variation with object size
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# - Results are sensitive to locking cost, but we dont
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# check for proper locking
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#
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import
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strutils, times
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type
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PNode = ref TNode
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TNode {.final.} = object
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left, right: PNode
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i, j: int
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proc newNode(L, r: PNode): PNode =
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new(result)
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result.left = L
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result.right = r
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const
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kStretchTreeDepth = 18 # about 16Mb
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kLongLivedTreeDepth = 16 # about 4Mb
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kArraySize = 500000 # about 4Mb
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kMinTreeDepth = 4
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kMaxTreeDepth = 16
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# Nodes used by a tree of a given size
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proc TreeSize(i: int): int = return ((1 shl (i + 1)) - 1)
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# Number of iterations to use for a given tree depth
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proc NumIters(i: int): int =
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return 2 * TreeSize(kStretchTreeDepth) div TreeSize(i)
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# Build tree top down, assigning to older objects.
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proc Populate(iDepth: int, thisNode: PNode) =
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if iDepth <= 0:
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return
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else:
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new(thisNode.left)
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new(thisNode.right)
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Populate(iDepth-1, thisNode.left)
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Populate(iDepth-1, thisNode.right)
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# Build tree bottom-up
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proc MakeTree(iDepth: int): PNode =
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if iDepth <= 0:
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new(result)
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else:
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return newNode(MakeTree(iDepth-1), MakeTree(iDepth-1))
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proc PrintDiagnostics() =
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echo("Total memory available: " & $getTotalMem() & " bytes")
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echo("Free memory: " & $getFreeMem() & " bytes")
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proc TimeConstruction(depth: int) =
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var
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root, tempTree: PNode
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iNumIters: int
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iNumIters = NumIters(depth)
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echo("Creating " & $iNumIters & " trees of depth " & $depth)
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var t = epochTime()
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for i in 0..iNumIters-1:
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new(tempTree)
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Populate(depth, tempTree)
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tempTree = nil
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echo("\tTop down construction took " & $(epochTime() - t) & "msecs")
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t = epochTime()
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for i in 0..iNumIters-1:
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tempTree = MakeTree(depth)
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tempTree = nil
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echo("\tBottom up construction took " & $(epochTime() - t) & "msecs")
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type
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tMyArray = seq[float]
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proc main() =
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var
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root, longLivedTree, tempTree: PNode
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myarray: tMyArray
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echo("Garbage Collector Test")
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echo(" Stretching memory with a binary tree of depth " & $kStretchTreeDepth)
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PrintDiagnostics()
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var t = epochTime()
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# Stretch the memory space quickly
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tempTree = MakeTree(kStretchTreeDepth)
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tempTree = nil
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# Create a long lived object
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echo(" Creating a long-lived binary tree of depth " &
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$kLongLivedTreeDepth)
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new(longLivedTree)
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Populate(kLongLivedTreeDepth, longLivedTree)
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# Create long-lived array, filling half of it
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echo(" Creating a long-lived array of " & $kArraySize & " doubles")
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newSeq(myarray, kArraySize)
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for i in 0..kArraySize div 2 -1:
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myarray[i] = 1.0 / toFloat(i)
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PrintDiagnostics()
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var d = kMinTreeDepth
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while d <= kMaxTreeDepth:
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TimeConstruction(d)
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inc(d, 2)
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if longLivedTree == nil or myarray[1000] != 1.0/1000.0:
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echo("Failed")
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# fake reference to LongLivedTree
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# and array to keep them from being optimized away
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var elapsed = epochTime() - t
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PrintDiagnostics()
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echo("Completed in " & $elapsed & "ms. Success!")
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when defined(GC_setMaxPause):
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GC_setMaxPause 2_000
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main()
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main()
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