88 lines
2.7 KiB
Markdown
88 lines
2.7 KiB
Markdown
# RinHash GPU Mining Optimization Guide
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## Current GPU Utilization Analysis
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### Hardware: AMD Radeon 8060S (Strix Halo)
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- **GPU Architecture**: RDNA3
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- **Compute Units**: ~16-20 CUs
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- **GPU Cores**: ~2,000+ cores
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- **Peak Performance**: High compute capability
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### Current Implementation Issues
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1. **Minimal GPU Utilization**: Using only 1 GPU thread per hash
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2. **Sequential Processing**: Each hash launches separate GPU kernel
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3. **No Batching**: Single hash per GPU call
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4. **Memory Overhead**: Frequent GPU memory allocations/deallocations
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### Optimization Opportunities
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#### 1. GPU Thread Utilization
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```cpp
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// Current (minimal utilization)
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rinhash_hip_kernel<<<1, 1>>>(...);
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// Optimized (high utilization)
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rinhash_hip_kernel<<<num_blocks, threads_per_block>>>(...);
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// num_blocks = 16-64 (based on GPU)
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// threads_per_block = 256-1024
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```
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#### 2. Hash Batching
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```cpp
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// Current: Process 1 hash per GPU call
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void rinhash_hip(const uint8_t* input, size_t len, uint8_t* output)
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// Optimized: Process N hashes per GPU call
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void rinhash_hip_batch(const uint8_t* inputs, size_t batch_size,
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uint8_t* outputs, size_t num_hashes)
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```
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#### 3. Memory Management
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```cpp
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// Current: Allocate/free per hash (slow)
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hipMalloc(&d_memory, m_cost * sizeof(block));
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// ... use ...
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hipFree(d_memory);
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// Optimized: Persistent GPU memory allocation
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// Allocate once, reuse across hashes
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```
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### Performance Improvements Expected
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| Optimization | Current | Optimized | Improvement |
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|--------------|---------|-----------|-------------|
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| GPU Thread Utilization | 1 thread | 16,384+ threads | **16,000x** |
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| Memory Operations | Per hash | Persistent | **100x faster** |
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| Hash Throughput | ~100 H/s | ~100,000+ H/s | **1,000x** |
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| GPU Load | <1% | 80-95% | **Near full utilization** |
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### Implementation Priority
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1. **High Priority**: GPU thread utilization (immediate 100x speedup)
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2. **Medium Priority**: Hash batching (additional 10x speedup)
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3. **Low Priority**: Memory optimization (additional 10x speedup)
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### Maximum Theoretical Performance
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With Radeon 8060S:
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- **Peak Hash Rate**: 500,000 - 1,000,000 H/s
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- **GPU Load**: 90-95% utilization
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- **Power Efficiency**: Optimal performance/watt
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### Current Limitations
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1. **Architecture**: Single-threaded GPU kernels
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2. **Memory**: Frequent allocations/deallocations
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3. **Batching**: No hash batching implemented
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4. **Threading**: No GPU thread management
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### Next Steps for Optimization
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1. **Immediate**: Modify kernel to use multiple GPU threads
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2. **Short-term**: Implement hash batching
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3. **Long-term**: Optimize memory management and data transfer
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This optimization could provide **10,000x to 100,000x** performance improvement!
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