- Update public methods signatures
- Remove 'lastAccess' param
- Add option to pass root for tree.Dump, Iterate, IterateWithStop,
Graphviz (and related)
- Move error messages to const defined error messages for external usage

Add dbgStats metrics to analyze number of Hashes, db Gets, and db Puts.

Current benchmarks:
```
CASE A, AddBatch was 8.841700 times faster than without AddBatch
	nCPU: 4, nLeafs: 1024, hash: Poseidon, db: memory
	dbgStats(hash: 2.044k, dbGet: 1, dbPut: 2.049k)
CASE B, AddBatch was 7.678766 times faster than without AddBatch
	nCPU: 4, nLeafs: 1024, hash: Poseidon, db: memory
	dbgStats(hash: 2.044k, dbGet: 199, dbPut: 2.049k)
CASE C, AddBatch was 8.401087 times faster than without AddBatch
	nCPU: 4, nLeafs: 1024, hash: Poseidon, db: memory
	dbgStats(hash: 2.044k, dbGet: 207, dbPut: 2.049k)
CASE D, AddBatch was 2.466346 times faster than without AddBatch
	nCPU: 4, nLeafs: 4096, hash: Poseidon, db: memory
	dbgStats(hash: 33.884k, dbGet: 30.697k, dbPut: 33.889k)
CASE E, AddBatch was 1.958160 times faster than without AddBatch
	nCPU: 4, nLeafs: 4096, hash: Poseidon, db: memory
	dbgStats(hash: 41.419k, dbGet: 37.558k, dbPut: 41.874k)
TestAddBatchBench: nCPU: 4, nLeafs: 50000, hash: Blake2b, db: leveldb
	Add loop:	10.089858449s
		dbgStats(hash: 825.285k, dbGet: 788.869k, dbPut: 925.285k)
	AddBatch:	904.647829ms
		dbgStats(hash: 122.458k, dbGet: 1, dbPut: 122.463k)
TestDbgStats
	add in loop    dbgStats(hash: 141.915k, dbGet: 134.602k, dbPut: 161.915k)
	addbatch caseA dbgStats(hash: 24.528k, dbGet: 1, dbPut: 24.533k)
	addbatch caseD dbgStats(hash: 115.506k, dbGet: 97.482k, dbPut: 115.516k)
```

- AddBatch use Virtual Tree for cases A,B,C
- ImportDump use AddBatch instead of adding one by one
- Reorg & add more virtual tree tests

- Replace naive AddBatch by optimized AddBatch
- Add blake2b hash support
- Expose needed methods for external usage (ReadLeafValue,
ReadIntermediateChilds)
- Return 'value' in GenProof

CASE D: Already populated Tree
==============================
- Use A, B, C, D as subtree
- Sort the Keys in Buckets that share the initial part of the path
- For each subtree add there the new leafs

              R
             /  \
            /    \
           /      \
          *        *
         / |      / \
        /  |     /   \
       /   |    /     \
L:    A    B   C       D
     /\   /\  / \     / \
    ...  ... ... ... ... ...

buildTreeBottomUp splits the key-values into n Buckets (where n is the
number of CPUs), in parallel builds a subtree for each bucket, once all
the subtrees are built, uses the subtrees roots as keys for a new tree,
which as result will have the complete Tree build from bottom to up,
where until the log2(nCPU) level it has been computed in parallel.

As result of this, the tree construction can be parallelized until
almost the top level, almost dividing the time by the number of CPUs.

CASE C: ALMOST CASE B --> if Tree has few Leafs (but numLeafs>=minLeafsThreshold)
==============================================================================
- Use A, B, G, F as Roots of subtrees
- Do CASE B for each subtree
- Then go from L to the Root

              R
             /  \
            /    \
           /      \
          *        *
         / |      / \
        /  |     /   \
       /   |    /     \
L:    A    B   G       D
              / \
             /   \
            /     \
           C      *
                 / \
                /   \
               /     \
              ...    ... (nLeafs >= minLeafsThreshold)