feature(parallel): add parallel plugin execution with resource-aware scheduling

[quinnjr]

Summary

Adds support for running independent pipeline plugins concurrently via explicit Parallel/EndParallel blocks in PluMA configuration files. This enables significant speedups for pipelines with independent processing steps while preserving PluMA's modular plugin architecture.

Key features

• Explicit parallel blocks — Parallel/EndParallel directives in config files with workers, memory, gpu, and fail options
• Fork-based process isolation — each plugin runs in its own process, avoiding Python GIL and R interpreter limitations
• Resource-aware scheduling — memory, GPU, and worker slot budgets prevent oversubscription
• Configurable failure modes — fail=fast (default) aborts on first error; fail=continue runs all tasks

Config syntax example

Prefix /data/pipeline
Plugin Normalize inputA.csv normalizedA.csv

Parallel workers=4 memory=8G fail=continue
  Plugin FeatureExtractA normalizedA.csv featuresA.csv
  Plugin FeatureExtractB normalizedB.csv featuresB.csv
  Plugin FeatureExtractC normalizedC.csv featuresC.csv
EndParallel

Plugin Merge featuresA.csv,featuresB.csv,featuresC.csv merged.csv

Components

File	Description
src/ParallelTypes.h	Core data structures (ParallelBlock, PluginTask, ResourceBudget, etc.)
src/ConfigParser.{h,cxx}	Parses config files including Parallel blocks, size strings, plugin tasks
src/ResourceBudget.{h,cxx}	Tracks and enforces memory/GPU/worker constraints
src/ParallelScheduler.{h,cxx}	Fork-based concurrent dispatch with signal handling and cleanup
tests/	67 Catch2 unit tests covering parser, budget, and scheduler
fuzz/	4 libFuzzer harnesses with seed corpus for parse_size, parse_config, parse_plugin_task, and resource_budget

Testing

• 67/67 unit tests passing (Catch2)
• Fuzz testing with libFuzzer + ASan/UBSan — found and fixed one crash in malformed option parsing
• Memory leak testing with AddressSanitizer/LeakSanitizer — zero findings

Test plan

• Review config parser behavior with existing PluMA pipeline files (backward compatibility)
• Integration test with actual PluMA plugins in parallel blocks
• Performance benchmarking with real bioinformatics workloads
• Test on multi-GPU systems for GPU slot scheduling
• Wire ConfigParser and ParallelScheduler into src/PluMA.cxx main loop

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