Make ForUtil Vectorized

### Description

Since the introduction of Vector API into Lucene via #12311, I have found it to be an interesting tool. As a result, I have attempted to use it to rewrite the [ForUtil.java](lucene/core/src/java/org/apache/lucene/codecs/lucene90/ForUtil.java) file. Initially, I attempted to port [simdcomp](https://github.com/lemire/simdcomp/blob/0c900190bbc0970f4342f2ea778564c95ca725cf/src/simdbitpacking.c) and implement pack and unpack for bitPerValue values that were less than or equal to 8. The results of my efforts can be seen below.
| Benchmark | Mode | Cnt | Score | Error | Units |
|-----------------------------|------|-------------|----------------|---------------|-------|
| VectorizeBenchmark.decode1 | thrpt | 15 | 58293945.447 | ± 1524549.587 | ops/s |
| VectorizeBenchmark.decode2 | thrpt | 15 | 55598229.538 | ± 4516920.135 | ops/s |
| VectorizeBenchmark.decode3 | thrpt | 15 | 57163871.965 | ± 1566246.490 | ops/s |
| VectorizeBenchmark.decode4 | thrpt | 15 | 55128874.528 | ± 4752397.170 | ops/s |
| VectorizeBenchmark.decode5 | thrpt | 15 | 53822335.729 | ± 4599217.489 | ops/s |
| VectorizeBenchmark.decode6 | thrpt | 15 | 48155246.120 | ± 7519360.551 | ops/s |
| VectorizeBenchmark.decode7 | thrpt | 15 | 50253799.192 | ± 820075.648 | ops/s |
| VectorizeBenchmark.decode8 | thrpt | 15 | 68849728.856 | ± 1818468.973 | ops/s |
| VectorizeBenchmark.encode1 | thrpt | 15 | 33998510.772 | ± 2924618.992 | ops/s |
| VectorizeBenchmark.encode2 | thrpt | 15 | 43238190.552 | ± 810373.966 | ops/s |
| VectorizeBenchmark.encode3 | thrpt | 15 | 36613553.485 | ± 483115.838 | ops/s |
| VectorizeBenchmark.encode4 | thrpt | 15 | 45675726.831 | ± 1081153.655 | ops/s |
| VectorizeBenchmark.encode5 | thrpt | 15 | 33591855.278 | ± 1084009.112 | ops/s |
| VectorizeBenchmark.encode6 | thrpt | 15 | 36110726.127 | ± 767075.709 | ops/s |
| VectorizeBenchmark.encode7 | thrpt | 15 | 34754339.379 | ± 275025.123 | ops/s |
| VectorizeBenchmark.encode8 | thrpt | 15 | 55075742.358 | ± 991165.320 | ops/s |
| VectorizeBenchmark.vectorizedDecode1 | thrpt | 15 | 43878020.796 | ± 7148545.623 | ops/s |
| VectorizeBenchmark.vectorizedDecode2 | thrpt | 15 | 103091446.773 | ± 44115190.011 | ops/s |
| VectorizeBenchmark.vectorizedDecode3 | thrpt | 15 | 83168059.373 | ± 24930903.852 | ops/s |
| VectorizeBenchmark.vectorizedDecode4 | thrpt | 15 | 63156089.355 | ± 15039408.293 | ops/s |
| VectorizeBenchmark.vectorizedDecode5 | thrpt | 15 | 96567546.695 | ± 37142784.493 | ops/s |
| VectorizeBenchmark.vectorizedDecode6 | thrpt | 15 | 73897063.180 | ± 11549757.437 | ops/s |
| VectorizeBenchmark.vectorizedDecode7 | thrpt | 15 | 79716185.567 | ± 29990852.039 | ops/s |
| VectorizeBenchmark.vectorizedDecode8 | thrpt | 15 | 92621676.617 | ± 29702056.667 | ops/s |
| VectorizeBenchmark.vectorizedEncode1 | thrpt | 15 | 51140300.852 | ± 139758.385 | ops/s |
| VectorizeBenchmark.vectorizedEncode2 | thrpt | 15 | 82646100.574 | ± 1289600.954 | ops/s |
| VectorizeBenchmark.vectorizedEncode3 | thrpt | 15 | 88124485.953 | ± 742170.198 | ops/s |
| VectorizeBenchmark.vectorizedEncode4 | thrpt | 15 | 91029285.467 | ± 5594858.437 | ops/s |
| VectorizeBenchmark.vectorizedEncode5 | thrpt | 15 | 96843051.648 | ± 8024430.836 | ops/s |
| VectorizeBenchmark.vectorizedEncode6 | thrpt | 15 | 98596724.128 | ± 10068466.227 | ops/s |
| VectorizeBenchmark.vectorizedEncode7 | thrpt | 15 | 85885746.715 | ± 6031740.563 | ops/s |
| VectorizeBenchmark.vectorizedEncode8 | thrpt | 15 | 117139889.194 | ± 8721517.095 | ops/s |

However, I noticed that the compression format used in [ForUtil.java](lucene/core/src/java/org/apache/lucene/codecs/lucene90/ForUtil.java) was different. It employed some tricks to speed up the process, such as simd. Therefore, I attempted to vectorize it while maintaining the compression format. The results can be seen below.
| Benchmark | Mode | Cnt | Score | Error | Units |
|-----------------------------|------|-----|----------------|----------------|-------|
| Benchmark.encode1 | thrpt | 15 | 38017254.040 | ± 3905466.628 | ops/s |
| Benchmark.encode2 | thrpt | 15 | 45170109.395 | ± 1539203.478 | ops/s |
| Benchmark.encode3 | thrpt | 15 | 38757256.653 | ± 1044709.221 | ops/s |
| Benchmark.encode4 | thrpt | 15 | 49307206.891 | ± 799168.007 | ops/s |
| Benchmark.encode5 | thrpt | 15 | 35130626.548 | ± 792210.817 | ops/s |
| Benchmark.encode6 | thrpt | 15 | 38326892.073 | ± 981865.963 | ops/s |
| Benchmark.encode7 | thrpt | 15 | 37372342.721 | ± 1177478.683 | ops/s |
| Benchmark.encode8 | thrpt | 15 | 60757390.416 | ± 458876.638 | ops/s |
| Benchmark.vectorizedEncode1 | thrpt | 15 | 56413094.655 | ± 435917.201 | ops/s |
| Benchmark.vectorizedEncode2 | thrpt | 15 | 88770400.646 | ± 11183716.176 | ops/s |
| Benchmark.vectorizedEncode3 | thrpt | 15 | 39932842.378 | ± 2366921.921 | ops/s |
| Benchmark.vectorizedEncode4 | thrpt | 15 | 85888128.739 | ± 5499354.172 | ops/s |
| Benchmark.vectorizedEncode5 | thrpt | 15 | 34402027.732 | ± 1414839.159 | ops/s |
| Benchmark.vectorizedEncode6 | thrpt | 15 | 35794303.501 | ± 782940.005 | ops/s |
| Benchmark.vectorizedEncode7 | thrpt | 15 | 33845690.180 | ± 2586648.353 | ops/s |
| Benchmark.vectorizedEncode8 | thrpt | 15 | 97914288.675 | ± 8971857.035 | ops/s |

I have only implemented bitPerValue values of 1, 2, 4, and 8. I am curious if it is possible to change the compression format. Additionally, do you have any best practices for integrating vectorized code into Lucene? Any suggestions would be appreciated.

Currently, I am working on my own [repo](https://github.com/tang-hi/forutil). However, the code is still in a rough state and lacks documentation.

Start by reading lucene/core/src/java/org/apache/lucene/codecs/lucene90/ForUtil.java, then compare the proposed approach in the linked pull request #12417 with the author's forutil repository. The issue does not define an accepted compression format, supported bit-per-value cases, or completion criteria, so those decisions must be settled before implementation.

Written by the indexing model from the issue text.