paracodex-cuda-ocl-step2

name	paracodex-cuda-ocl-step2
description	ParaCodex prompt for cuda ocl step2 step.

Performance Tuning - CUDA to OpenCL Migration

Directory: {kernel_dir}/
Files: {file_listing}
Profile: {profile_log_path} Reference: {kernel_dir}/opencl_migration_plan.md

Context

Migrated from CUDA → OpenCL. Differences in runtime, compiler, and memory handling often cause performance gaps.

Workflow

1. Verify Baseline Correctness

cd {kernel_dir}
{clean_cmd_str}
timeout 300 {correctness_run_cmd} > current_output.txt 2>&1
diff baseline_output.txt current_output.txt

If errors, fix correctness issues before optimization.

2. Analyze Performance Profile

1. Read profile data (cat {profile_log_path} | grep ...).
2. Compare with CUDA baseline.
3. If >1.5x slowdown: Significant optimization needed.
4. Compare kernel time to end-to-end runtime; if they diverge, check structural issues before micro-tuning.
5. Recheck with at least one larger practical input when hardware and timeout budget allow; choose a size that materially exercises the GPU on the available hardware rather than one that remains launch-dominated, and reject changes that only win on the smallest/default run.
6. Use system_info_summary.txt to size that run against the actual device. Prefer the largest short-run, memory-safe input that should load the GPU meaningfully, not merely a modest increase over the default.

3. Create Optimization Plan

MANDATORY: Create optimization_plan.md in {kernel_dir} using template in references/output.md. Reference: references/examples.md (Bottleneck Analysis).

Analyses to check:

• Work-Group Size Suboptimal?
• Memory Transfer Overhead?
• Math Function Precision?
• Local Memory Bank Conflicts?
• Kernel Launch Overhead?
• Wrong kernel/program split?

4. Execute Optimizations

Reference: references/examples.md (Optimization Examples).

• 4A. Optimize Work-Group Size: Query CL_KERNEL_PREFERRED_WORK_GROUP_SIZE_MULTIPLE and set local_work_size to a multiple of it.
• 4S. Structural Rewrite: Fuse kernels, move build/setup out of the hot path, or replace a weak step1 split before micro-optimizing.
• 4B. Native Math: Use native_sin, native_cos, native_sqrt where precision allows (avoids IEEE-754 overhead).
• 4C. Transfers: Use CL_MEM_ALLOC_HOST_PTR (pinned) buffers; use clEnqueueWriteBuffer with CL_FALSE (non-blocking) + events for async.
• 4D. Barriers: Use CLK_LOCAL_MEM_FENCE over CLK_GLOBAL_MEM_FENCE when only local memory requires synchronization.
• 4E. Vector Loads: Use float4/int4 types for memory reads/writes to improve coalescing and instruction throughput.
• Micro-Opts: restrict, private variable caching of repeated global reads, #pragma unroll.
• Reject any change that improves only the tiny/default run but scales worse at the larger practical input.
• Do not accept a "larger" input that still leaves the GPU mostly idle. If utilization is still weak, push higher within the short-run budget and record the hardware/memory reason if you stop.

5. Verify & Profile (Iterative)

{clean_cmd_str}
{build_cmd_str}
timeout 300 {run_cmd_str} > optimized_output.txt 2>&1
diff baseline_output.txt optimized_output.txt
{profile_cmd_str} > {profile_log_path}_optimized 2>&1

6. Final Summary

Update optimization_plan.md using "Final Performance Summary" template, including whether larger-input profiling changed the decision.

Rules

• NO GIT COMMANDS
• DO NOT READ/WRITE OUTSIDE THE WORKING DIRECTORY
• ALWAYS CLEAN BEFORE BUILD
• PRESERVE CORRECTNESS - diff against baseline after each change.
• VERIFY PERFORMANCE GAIN - revert if slower.