Single-Thread Writer: Simplifying Parallel HDF5 I/O

HDF5 has a global lock: no matter how many threads you spawn, only one can execute HDF5 library calls at a time. If you naïvely let multiple threads hammer the library, you get serialization at best and deadlocks at worst.

The solution? One writer thread. All producers hand off data to it via a queue; it alone touches the HDF5 API.

Design Pattern

Producers (sensor readers, network handlers, simulators) run freely.
They push their data into a lock-free or bounded queue.
A single dedicated writer thread pops from the queue and performs all HDF5 calls (H5Dwrite, H5Dset_extent, etc.).

This way, the library never sees concurrent calls, and your application avoids global-lock contention.

Example Flow

```cpp // producers void producer(queue_t& q, int id) { for (int i = 0; i < 100; i++) { record_t rec{id, i}; q.push(rec); } }

// consumer/writer void writer(queue_t& q, h5::ds_t& ds) { record_t rec; while (q.pop(rec)) { h5::append(ds, rec); // all HDF5 I/O is serialized here } } ````

Thread Coordination

Producers run independently.
The writer drains the queue at its own pace.
When producers finish, they signal termination, and the writer flushes any remaining data before closing the file.

Benefits

✅ Correctness: no race conditions inside HDF5.
✅ Performance: eliminates global-lock thrashing.
✅ Simplicity: no need for per-thread file handles or MPI gymnastics.

In practice, a well-implemented queue keeps throughput high enough to saturate disk bandwidth. For bursty workloads, batching writes can further smooth performance.

When to Use

Multithreaded producers feeding a single HDF5 container.
Applications where correctness and predictability outweigh fine-grained parallel writes.
Prototypes that may later evolve into MPI-based distributed writers.

Takeaway

HDF5 isn’t thread-parallel—but your architecture can be. Push all I/O through a single writer thread, and let your other threads do what they do best: generate data without blocking.