Package org.apache.sysds.hops

Class OptimizerUtils

java.lang.Object
org.apache.sysds.hops.OptimizerUtils
public class OptimizerUtils extends Object

  • Field Details

    • MEM_UTIL_FACTOR

      public static double MEM_UTIL_FACTOR
      Utilization factor used in deciding whether an operation to be scheduled on CP or MR. NOTE: it is important that MEM_UTIL_FACTOR+CacheableData.CACHING_BUFFER_SIZE < 1.0

    • DEFAULT_MEM_UTIL_FACTOR

      public static double DEFAULT_MEM_UTIL_FACTOR
      Default buffer pool sizes for static (15%) and unified (85%) memory

    • DEFAULT_UMM_UTIL_FACTOR

      public static double DEFAULT_UMM_UTIL_FACTOR

    • MEMORY_MANAGER

      public static OptimizerUtils.MemoryManager MEMORY_MANAGER
      Indicate the current memory manager in effect

    • BUFFER_POOL_SIZE

      public static long BUFFER_POOL_SIZE
      Buffer pool size in bytes

    • DEFAULT_BLOCKSIZE

      public static final int DEFAULT_BLOCKSIZE
      Default blocksize if unspecified or for testing purposes
      See Also:

    • DEFAULT_FRAME_BLOCKSIZE

      public static final int DEFAULT_FRAME_BLOCKSIZE
      Default frame blocksize
      See Also:

    • DEFAULT_OPTLEVEL

      public static final OptimizerUtils.OptimizationLevel DEFAULT_OPTLEVEL
      Default optimization level if unspecified

    • DEFAULT_SIZE

      public static double DEFAULT_SIZE
      Default memory size, which is used if the actual estimate can not be computed e.g., when input/output dimensions are unknown. The default is set to a large value so that operations are scheduled on MR while avoiding overflows as well.

    • DOUBLE_SIZE

      public static final long DOUBLE_SIZE
      See Also:

    • INT_SIZE

      public static final long INT_SIZE
      See Also:

    • CHAR_SIZE

      public static final long CHAR_SIZE
      See Also:

    • BOOLEAN_SIZE

      public static final long BOOLEAN_SIZE
      See Also:

    • INVALID_SIZE

      public static final double INVALID_SIZE
      See Also:

    • MAX_NUMCELLS_CP_DENSE

      public static final long MAX_NUMCELLS_CP_DENSE
      See Also:

    • MAX_NNZ_CP_SPARSE

      public static final long MAX_NNZ_CP_SPARSE

    • SAFE_REP_CHANGE_THRES

      public static final long SAFE_REP_CHANGE_THRES
      See Also:

    • ALLOW_COMMON_SUBEXPRESSION_ELIMINATION

      public static boolean ALLOW_COMMON_SUBEXPRESSION_ELIMINATION
      Enables common subexpression elimination in dags. There is however, a potential tradeoff between computation redundancy and data transfer between MR jobs. Since, we do not reason about transferred data yet, this rewrite rule is enabled by default.

    • ALLOW_CONSTANT_FOLDING

      public static boolean ALLOW_CONSTANT_FOLDING
      Enables constant folding in dags. Constant folding computes simple expressions of binary operations and literals and replaces the hop sub-DAG with a new literal operator.

    • ALLOW_ALGEBRAIC_SIMPLIFICATION

      public static boolean ALLOW_ALGEBRAIC_SIMPLIFICATION

    • ALLOW_OPERATOR_FUSION

      public static boolean ALLOW_OPERATOR_FUSION

    • ALLOW_BRANCH_REMOVAL

      public static boolean ALLOW_BRANCH_REMOVAL
      Enables if-else branch removal for constant predicates (original literals or results of constant folding).

    • ALLOW_FOR_LOOP_REMOVAL

      public static boolean ALLOW_FOR_LOOP_REMOVAL
      Enables the removal of (par)for-loops when from, to, and increment are constants (original literals or results of constant folding) and lead to an empty sequence, i.e., (par)for-loops without a single iteration.

    • ALLOW_AUTO_VECTORIZATION

      public static boolean ALLOW_AUTO_VECTORIZATION

    • ALLOW_SIZE_EXPRESSION_EVALUATION

      public static boolean ALLOW_SIZE_EXPRESSION_EVALUATION
      Enables simple expression evaluation for datagen parameters 'rows', 'cols'. Simple expressions are defined as binary operations on literals and nrow/ncol. This applies only to exact size information.

    • ALLOW_WORSTCASE_SIZE_EXPRESSION_EVALUATION

      public static boolean ALLOW_WORSTCASE_SIZE_EXPRESSION_EVALUATION
      Enables simple expression evaluation for datagen parameters 'rows', 'cols'. Simple expressions are defined as binary operations on literals and b(+) or b(*) on nrow/ncol. This applies also to worst-case size information.

    • ALLOW_RAND_JOB_RECOMPILE

      public static boolean ALLOW_RAND_JOB_RECOMPILE

    • ALLOW_RUNTIME_PIGGYBACKING

      public static boolean ALLOW_RUNTIME_PIGGYBACKING
      Enables parfor runtime piggybacking of MR jobs into the packed jobs for scan sharing.

    • ALLOW_INTER_PROCEDURAL_ANALYSIS

      public static boolean ALLOW_INTER_PROCEDURAL_ANALYSIS
      Enables interprocedural analysis between main script and functions as well as functions and other functions. This includes, for example, to propagate statistics into functions if save to do so (e.g., if called once).

    • IPA_NUM_REPETITIONS

      public static int IPA_NUM_REPETITIONS
      Number of inter-procedural analysis (IPA) repetitions. If set to >=2, we apply IPA multiple times in order to allow scalar propagation over complex function call graphs and various interactions between constant propagation, constant folding, and other rewrites such as branch removal and the merge of statement block sequences.

    • ALLOW_SUM_PRODUCT_REWRITES

      public static boolean ALLOW_SUM_PRODUCT_REWRITES
      Enables sum product rewrites such as mapmultchains. In the future, this will cover all sum-product related rewrites.

    • ALLOW_SUM_PRODUCT_REWRITES2

      public static boolean ALLOW_SUM_PRODUCT_REWRITES2

    • ALLOW_ADVANCED_MMCHAIN_REWRITES

      public static boolean ALLOW_ADVANCED_MMCHAIN_REWRITES
      Enables additional mmchain optimizations. In the future, this might be merged with ALLOW_SUM_PRODUCT_REWRITES.

    • ALLOW_NEW_MMCHAIN_REWRITE

      public static boolean ALLOW_NEW_MMCHAIN_REWRITE
      Enables a DPSize inspired algorithm rewrite for MMChain with transposes

    • ALLOW_SPLIT_HOP_DAGS

      public static boolean ALLOW_SPLIT_HOP_DAGS
      Enables a specific hop dag rewrite that splits hop dags after csv persistent reads with unknown size in order to allow for recompile.

    • ALLOW_LOOP_UPDATE_IN_PLACE

      public static boolean ALLOW_LOOP_UPDATE_IN_PLACE
      Enables a specific rewrite that enables update in place for loop variables that are only read/updated via cp leftindexing.

    • ALLOW_UNARY_UPDATE_IN_PLACE

      public static boolean ALLOW_UNARY_UPDATE_IN_PLACE
      Enables the update-in-place for all unary operators with a single consumer. In this case we do not allocate the output, but directly write the output values back to the input block.

    • ALLOW_BINARY_UPDATE_IN_PLACE

      public static boolean ALLOW_BINARY_UPDATE_IN_PLACE
      Enables update-in-place for binary operators if the first input has no consumers. In this case we directly write the output values back to the first input block.

    • ALLOW_EVAL_FCALL_REPLACEMENT

      public static boolean ALLOW_EVAL_FCALL_REPLACEMENT
      Replace eval second-order function calls with normal function call if the function name is a known string (after constant propagation).

    • ALLOW_CODE_MOTION

      public static boolean ALLOW_CODE_MOTION
      Enables a specific rewrite for code motion, i.e., hoisting loop invariant code out of while, for, and parfor loops.

    • FEDERATED_COMPILATION

      public static boolean FEDERATED_COMPILATION
      Compile federated instructions based on input federation state and privacy constraints.

    • FEDERATED_SPECS

      public static Map<Integer,FEDInstruction.FederatedOutput> FEDERATED_SPECS

    • PARALLEL_CP_READ_PARALLELISM_MULTIPLIER

      public static final double PARALLEL_CP_READ_PARALLELISM_MULTIPLIER
      Specifies a multiplier computing the degree of parallelism of parallel text read/write out of the available degree of parallelism. Set it to 1.0 to get a number of threads equal the number of virtual cores.
      See Also:

    • PARALLEL_CP_WRITE_PARALLELISM_MULTIPLIER

      public static final double PARALLEL_CP_WRITE_PARALLELISM_MULTIPLIER
      See Also:

    • ALLOW_COMBINE_FILE_INPUT_FORMAT

      public static final boolean ALLOW_COMBINE_FILE_INPUT_FORMAT
      Enables the use of CombineSequenceFileInputFormat with splitsize = 2x hdfs blocksize, if sort buffer size large enough and parallelism not hurt. This solves to issues: (1) it combines small files (depending on producers), and (2) it reduces task latency of large jobs with many tasks by factor 2.
      See Also:

    • ALLOW_SCRIPT_LEVEL_LOCAL_COMMAND

      public static boolean ALLOW_SCRIPT_LEVEL_LOCAL_COMMAND
      This variable allows for use of explicit local command, that forces a spark block to be executed and returned as a local block.

    • ALLOW_SCRIPT_LEVEL_COMPRESS_COMMAND

      public static boolean ALLOW_SCRIPT_LEVEL_COMPRESS_COMMAND
      This variable allows for insertion of Compress and decompress in the dml script from the user. This is added because we want to have a way to test, and verify the correct placement of compress and decompress commands.

    • ALLOW_SCRIPT_LEVEL_QUANTIZE_COMPRESS_COMMAND

      public static boolean ALLOW_SCRIPT_LEVEL_QUANTIZE_COMPRESS_COMMAND
      This variable allows for insertion of Quantize and compress in the dml script from the user.

    • ALLOW_QUANTIZE_COMPRESS_REWRITE

      public static boolean ALLOW_QUANTIZE_COMPRESS_REWRITE
      Boolean specifying if quantization-fused compression rewrite is allowed.

    • ALLOW_COMPRESSION_REWRITE

      public static boolean ALLOW_COMPRESSION_REWRITE
      Boolean specifying if compression rewrites is allowed. This is disabled at run time if the IPA for Workload aware compression is activated.

    • ALLOW_TRANSITIVE_SPARK_EXEC_TYPE

      public static boolean ALLOW_TRANSITIVE_SPARK_EXEC_TYPE
      Enable transitive spark execution type selection. This refines the exec-type selection logic of unary aggregates by pushing * the unary aggregates, whose inputs are created by spark instructions, to spark execution type as well.

    • ALLOW_JOIN_REORDERING_REWRITE

      public static boolean ALLOW_JOIN_REORDERING_REWRITE

    • ASYNC_PREFETCH

      public static boolean ASYNC_PREFETCH
      Enable prefetch and broadcast. Prefetch asynchronously calls acquireReadAndRelease() to trigger remote operations, which would otherwise make the next instruction wait till completion. Broadcast allows asynchronously transferring the data to all the nodes.

    • ASYNC_BROADCAST_SPARK

      public static boolean ASYNC_BROADCAST_SPARK

    • ASYNC_CHECKPOINT_SPARK

      public static boolean ASYNC_CHECKPOINT_SPARK

    • MAX_PARALLELIZE_ORDER

      public static boolean MAX_PARALLELIZE_ORDER
      Heuristic-based instruction ordering to maximize inter-operator PARALLELISM. Place the Spark operator chains first and trigger them to execute in parallel.

    • COST_BASED_ORDERING

      public static boolean COST_BASED_ORDERING
      Cost-based instruction ordering to minimize total execution time under the constraint of available memory.

    • RULE_BASED_GPU_EXEC

      public static boolean RULE_BASED_GPU_EXEC
      Rule-based operator placement policy for GPU.

    • AUTO_GPU_CACHE_EVICTION

      public static boolean AUTO_GPU_CACHE_EVICTION
      Automatic placement of GPU lineage cache eviction

    • ALLOW_RA_REWRITES

      public static boolean ALLOW_RA_REWRITES
      Boolean specifying if relational algebra rewrites are allowed (e.g. Selection Pushdowns).

  • Constructor Details

    • OptimizerUtils

      public OptimizerUtils()

  • Method Details

    • getOptLevel

      public static OptimizerUtils.OptimizationLevel getOptLevel()

    • isMemoryBasedOptLevel

      public static boolean isMemoryBasedOptLevel()

    • isOptLevel

      public static boolean isOptLevel(OptimizerUtils.OptimizationLevel level)

    • constructCompilerConfig

      public static CompilerConfig constructCompilerConfig(DMLConfig dmlconf)

    • constructCompilerConfig

      public static CompilerConfig constructCompilerConfig(CompilerConfig cconf, DMLConfig dmlconf)

    • resetStaticCompilerFlags

      public static void resetStaticCompilerFlags()

    • getDefaultSize

      public static long getDefaultSize()

    • resetDefaultSize

      public static void resetDefaultSize()

    • getDefaultFrameSize

      public static int getDefaultFrameSize()

    • getLocalMemBudget

      public static double getLocalMemBudget()
      Returns memory budget (according to util factor) in bytes
      Returns:
      local memory budget

    • getBufferPoolLimit

      public static long getBufferPoolLimit()
      Returns buffer pool size as set in the config
      Returns:
      buffer pool size in bytes

    • isUMMEnabled

      public static boolean isUMMEnabled()
      Check if unified memory manager is in effect
      Returns:
      boolean

    • disableUMM

      public static void disableUMM()
      Disable unified memory manager and fallback to static partitioning. Initialize LazyWriteBuffer with the default size (15%).

    • enableUMM

      public static void enableUMM()
      Enable unified memory manager and initialize with the default size (85%).

    • isMaxLocalParallelism

      public static boolean isMaxLocalParallelism(int k)

    • isTopLevelParFor

      public static boolean isTopLevelParFor()

    • checkSparkBroadcastMemoryBudget

      public static boolean checkSparkBroadcastMemoryBudget(double size)

    • checkSparkBroadcastMemoryBudget

      public static boolean checkSparkBroadcastMemoryBudget(long rlen, long clen, long blen, long nnz)

    • checkSparkCollectMemoryBudget

      public static boolean checkSparkCollectMemoryBudget(DataCharacteristics dc, long memPinned)

    • checkSparkCollectMemoryBudget

      public static boolean checkSparkCollectMemoryBudget(DataCharacteristics dc, long memPinned, boolean checkBP)

    • checkSparseBlockCSRConversion

      public static boolean checkSparseBlockCSRConversion(DataCharacteristics dcIn)

    • getNumTasks

      public static int getNumTasks()
      Returns the number of tasks that potentially run in parallel. This is either just the configured value (SystemDS config) or the minimum of configured value and available task slots.
      Returns:
      number of tasks

    • getDefaultExecutionMode

      public static Types.ExecMode getDefaultExecutionMode()

    • isSparkExecutionMode

      public static boolean isSparkExecutionMode()

    • isHybridExecutionMode

      public static boolean isHybridExecutionMode()

    • getParallelTextReadParallelism

      public static int getParallelTextReadParallelism()
      Returns the degree of parallelism used for parallel text read. This is computed as the number of virtual cores scales by the PARALLEL_READ_PARALLELISM_MULTIPLIER. If PARALLEL_READ_TEXTFORMATS is disabled, this method returns 1.
      Returns:
      degree of parallelism

    • getParallelBinaryReadParallelism

      public static int getParallelBinaryReadParallelism()

    • getParallelTextWriteParallelism

      public static int getParallelTextWriteParallelism()
      Returns the degree of parallelism used for parallel text write. This is computed as the number of virtual cores scales by the PARALLEL_WRITE_PARALLELISM_MULTIPLIER. If PARALLEL_WRITE_TEXTFORMATS is disabled, this method returns 1.
      Returns:
      degree of parallelism

    • getParallelBinaryWriteParallelism

      public static int getParallelBinaryWriteParallelism()

    • estimateSize

      public static long estimateSize(DataCharacteristics dc)

    • estimateSizeExactSparsity

      public static long estimateSizeExactSparsity(DataCharacteristics dc)

    • estimateSizeExactSparsity

      public static long estimateSizeExactSparsity(long nrows, long ncols, long nnz)
      Estimates the footprint (in bytes) for an in-memory representation of a matrix with dimensions=(nrows,ncols) and and number of non-zeros nnz.
      Parameters:
      nrows - number of rows
      ncols - number of cols
      nnz - number of non-zeros
      Returns:
      memory footprint

    • estimateSizeExactFrame

      public static long estimateSizeExactFrame(long nRows, long nCols)

    • estimateSizeExactSparsity

      public static long estimateSizeExactSparsity(long nrows, long ncols, double sp)
      Estimates the footprint (in bytes) for an in-memory representation of a matrix with dimensions=(nrows,ncols) and sparsity=sp. This function can be used directly in Hops, when the actual sparsity is known i.e., sp is guaranteed to give worst-case estimate (e.g., Rand with a fixed sparsity). In all other cases, estimateSize() must be used so that worst-case estimates are computed, whenever applicable.
      Parameters:
      nrows - number of rows
      ncols - number of cols
      sp - sparsity
      Returns:
      memory footprint

    • estimateSizeExactSparsity

      public static long estimateSizeExactSparsity(long nrows, long ncols, double sp, Types.DataType dt)

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(DataCharacteristics dc)
      Estimates the footprint (in bytes) for a partitioned in-memory representation of a matrix with the given matrix characteristics
      Parameters:
      dc - matrix characteristics
      Returns:
      memory estimate

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(DataCharacteristics dc, boolean outputEmptyBlocks)

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(long rlen, long clen, long blen, long nnz)
      Estimates the footprint (in bytes) for a partitioned in-memory representation of a matrix with dimensions=(nrows,ncols) and number of non-zeros nnz.
      Parameters:
      rlen - number of rows
      clen - number of cols
      blen - rows/cols per block
      nnz - number of non-zeros
      Returns:
      memory estimate

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(long rlen, long clen, long blen, long nnz, boolean outputEmptyBlocks)

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(Hop hop)
      Estimates the footprint (in bytes) for a partitioned in-memory representation of a matrix with the hops dimensions and number of non-zeros nnz.
      Parameters:
      hop - The hop to extract dimensions and nnz from
      Returns:
      the memory estimate

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(long rlen, long clen, long blen, double sp)
      Estimates the footprint (in bytes) for a partitioned in-memory representation of a matrix with dimensions=(nrows,ncols) and sparsity=sp.
      Parameters:
      rlen - number of rows
      clen - number of cols
      blen - rows/cols per block
      sp - sparsity
      Returns:
      memory estimate

    • estimatePartitionedSizeExactSparsity

      public static long estimatePartitionedSizeExactSparsity(long rlen, long clen, long blen, double sp, boolean outputEmptyBlocks)

    • estimateSize

      public static long estimateSize(long nrows, long ncols)
      Similar to estimate() except that it provides worst-case estimates when the optimization type is ROBUST.
      Parameters:
      nrows - number of rows
      ncols - number of cols
      Returns:
      memory estimate

    • estimateSizeEmptyBlock

      public static long estimateSizeEmptyBlock(long nrows, long ncols)

    • estimateSizeTextOutput

      public static long estimateSizeTextOutput(long rows, long cols, long nnz, Types.FileFormat fmt)

    • estimateSizeTextOutput

      public static long estimateSizeTextOutput(int[] dims, long nnz, Types.FileFormat fmt)

    • getTotalMemEstimate

      public static double getTotalMemEstimate(Hop[] in, Hop out)

    • getTotalMemEstimate

      public static double getTotalMemEstimate(Hop[] in, Hop out, boolean denseOut)

    • isIndexingRangeBlockAligned

      public static boolean isIndexingRangeBlockAligned(IndexRange ixrange, DataCharacteristics mc)
      Indicates if the given indexing range is block aligned, i.e., it does not require global aggregation of blocks.
      Parameters:
      ixrange - indexing range
      mc - matrix characteristics
      Returns:
      true if indexing range is block aligned

    • isIndexingRangeBlockAligned

      public static boolean isIndexingRangeBlockAligned(long rl, long ru, long cl, long cu, long blen)
      Indicates if the given indexing range is block aligned, i.e., it does not require global aggregation of blocks.
      Parameters:
      rl - rows lower
      ru - rows upper
      cl - cols lower
      cu - cols upper
      blen - rows/cols per block
      Returns:
      true if indexing range is block aligned

    • isValidCPDimensions

      public static boolean isValidCPDimensions(DataCharacteristics mc)

    • isValidCPDimensions

      public static boolean isValidCPDimensions(long rows, long cols)
      Returns false if dimensions known to be invalid; other true
      Parameters:
      rows - number of rows
      cols - number of cols
      Returns:
      true if dimensions valid

    • isValidCPDimensions

      public static boolean isValidCPDimensions(Types.ValueType[] schema, String[] names)
      Returns false if schema and names are not properly specified; other true Length to be > 0, and length of both to be equal.
      Parameters:
      schema - the schema
      names - the names
      Returns:
      false if schema and names are not properly specified

    • isValidCPMatrixSize

      public static boolean isValidCPMatrixSize(long rows, long cols, double sparsity)
      Determines if valid matrix size to be represented in CP data structures. Note that sparsity needs to be specified as rows*cols if unknown.
      Parameters:
      rows - number of rows
      cols - number of cols
      sparsity - the sparsity
      Returns:
      true if valid matrix size

    • exceedsCachingThreshold

      public static boolean exceedsCachingThreshold(long dim2, double outMem)
      Indicates if the given matrix characteristics exceed the threshold for caching, i.e., the matrix should be cached.
      Parameters:
      dim2 - dimension 2
      outMem - ?
      Returns:
      true if the given matrix characteristics exceed threshold

    • getUniqueTempFileName

      public static String getUniqueTempFileName()
      Wrapper over internal filename construction for external usage.
      Returns:
      unique temp file name

    • allowsToFilterEmptyBlockOutputs

      public static boolean allowsToFilterEmptyBlockOutputs(Hop hop)

    • getConstrainedNumThreads

      public static int getConstrainedNumThreads(int maxNumThreads)

    • getTransformNumThreads

      public static int getTransformNumThreads()

    • getTokenizeNumThreads

      public static int getTokenizeNumThreads()

    • getDefaultLogLevel

      public static org.apache.log4j.Level getDefaultLogLevel()

    • getMatMultNnz

      public static long getMatMultNnz(double sp1, double sp2, long m, long k, long n, boolean worstcase)

    • getMatMultSparsity

      public static double getMatMultSparsity(double sp1, double sp2, long m, long k, long n, boolean worstcase)
      Estimates the result sparsity for Matrix Multiplication A %*% B.
      Parameters:
      sp1 - sparsity of A
      sp2 - sparsity of B
      m - nrow(A)
      k - ncol(A), nrow(B)
      n - ncol(B)
      worstcase - true if worst case
      Returns:
      the sparsity

    • getLeftIndexingSparsity

      public static double getLeftIndexingSparsity(long rlen1, long clen1, long nnz1, long rlen2, long clen2, long nnz2)

    • isBinaryOpConditionalSparseSafe

      public static boolean isBinaryOpConditionalSparseSafe(Types.OpOp2 op)
      Determines if a given binary op is potentially conditional sparse safe.
      Parameters:
      op - the HOP OpOp2
      Returns:
      true if potentially conditional sparse safe

    • isBinaryOpConditionalSparseSafeExact

      public static boolean isBinaryOpConditionalSparseSafeExact(Types.OpOp2 op, LiteralOp lit)
      Determines if a given binary op with scalar literal guarantee an output sparsity which is exactly the same as its matrix input sparsity.
      Parameters:
      op - the HOP OpOp2
      lit - literal operator
      Returns:
      true if output sparsity same as matrix input sparsity

    • isBinaryOpSparsityConditionalSparseSafe

      public static boolean isBinaryOpSparsityConditionalSparseSafe(Types.OpOp2 op, LiteralOp lit)

    • getBinaryOpSparsityConditionalSparseSafe

      public static double getBinaryOpSparsityConditionalSparseSafe(double sp1, Types.OpOp2 op, LiteralOp lit)

    • getBinaryOpSparsity

      public static double getBinaryOpSparsity(double sp1, double sp2, Types.OpOp2 op, boolean worstcase)
      Estimates the result sparsity for matrix-matrix binary operations (A op B)
      Parameters:
      sp1 - sparsity of A
      sp2 - sparsity of B
      op - binary operation
      worstcase - true if worst case
      Returns:
      result sparsity for matrix-matrix binary operations

    • getOuterNonZeros

      public static long getOuterNonZeros(long n1, long n2, long nnz1, long nnz2, Types.OpOp2 op)

    • getNnz

      public static long getNnz(long dim1, long dim2, double sp)

    • getSparsity

      public static double getSparsity(DataCharacteristics dc)

    • getSparsity

      public static double getSparsity(long dim1, long dim2, long nnz)

    • getSparsity

      public static double getSparsity(Hop hop)

    • getSparsity

      public static double getSparsity(long[] dims, long nnz)

    • toMB

      public static String toMB(double inB)

    • getNumIterations

      public static long getNumIterations(ForProgramBlock fpb, long defaultValue)

    • getNumIterations

      public static long getNumIterations(ForStatementBlock fsb, long defaultValue)

    • getNumIterations

      public static long getNumIterations(ForProgramBlock fpb, LocalVariableMap vars, long defaultValue)

    • rEvalSimpleLongExpression

      public static long rEvalSimpleLongExpression(Hop root, Map<Long,Long> valMemo)
      Function to evaluate simple size expressions over literals and now/ncol. It returns the exact results of this expressions if known, otherwise Long.MAX_VALUE if unknown.
      Parameters:
      root - the root high-level operator
      valMemo - ?
      Returns:
      size expression

    • rEvalSimpleLongExpression

      public static long rEvalSimpleLongExpression(Hop root, Map<Long,Long> valMemo, LocalVariableMap vars)

    • rEvalSimpleDoubleExpression

      public static double rEvalSimpleDoubleExpression(Hop root, Map<Long,Double> valMemo)

    • rEvalSimpleDoubleExpression

      public static double rEvalSimpleDoubleExpression(Hop root, Map<Long,Double> valMemo, LocalVariableMap vars)