How to find the most profitable algorithm for your specific GPU?

Finding Optimal Mining Algorithms

1. GPU architecture dictates algorithm compatibility and efficiency. NVIDIA’s Ampere and Ada Lovelace series deliver superior hash rates on Ethash-derived algorithms before the Ethereum merge, while AMD RDNA2 and RDNA3 chips often outperform on KawPoW and Autolykos variants.

2. Driver version and firmware updates directly influence kernel launch latency and memory bandwidth utilization. A mismatched CUDA toolkit version can reduce DaggerHashimoto throughput by up to 18% on RTX 4090 systems.

3. Memory bandwidth saturation becomes a bottleneck when mining memory-hard algorithms like RandomX or ProgPoW. GPUs with GDDR6X memory and 384-bit bus width consistently maintain higher stable clocks under sustained load.

4. Power limit tuning interacts nonlinearly with algorithm-specific memory access patterns. Lowering TDP by 15% may improve kWh/TH on CuckooCycle but degrade performance on BeamHash III due to reduced L2 cache hit rates.

5. Kernel compilation flags affect register allocation and warp scheduling. Manually compiled ccminer binaries with -use_fast_math disabled yield 4.2% higher hashrates on Equihash-144,5 for Radeon RX 7900 XTX.

Benchmarking Methodology

1. Isolate variables by disabling background processes, setting fixed GPU clocks, and using identical memory timings across test runs.

2. Run each algorithm for a minimum of 45 minutes to account for thermal throttling cycles and driver-level memory fragmentation effects.

3. Record both average hashrate and standard deviation—algorithms with low variance indicate better scheduler predictability and lower stale share rates.

4. Measure wall-clock power consumption at the PSU input using a calibrated Kill-A-Watt meter rather than relying on GPU-Z sensor readings.

5. Cross-validate results across multiple miner clients: T-Rex, GMiner, and TeamRedMiner often report divergent hashrates for identical binaries due to differing memory copy strategies.

Algorithm-Specific GPU Behavior

1. Ethash derivatives stress VRAM bandwidth and latency—GPUs with HBM2e memory show 22% higher effective bandwidth utilization compared to GDDR6 counterparts under equivalent DAG sizes.

2. RandomX relies heavily on L3 cache size and CPU-GPU co-processing; integrated APUs with shared memory architecture achieve 30% higher efficiency per watt than discrete GPU-only setups.

3. Cuckatoo31 and Cuckatoo32 favor high-bandwidth memory interfaces with low-latency address translation units—AMD MI210 accelerates these by 3.7x over consumer-grade Radeon VII despite similar theoretical bandwidth.

4. BeamHash III execution time correlates strongly with FP64 throughput in compute mode; Tesla V100s outperform RTX 4090 by 19% despite lower memory bandwidth due to dedicated double-precision units.

5. Zcash-equivalent Equihash variants exhibit sensitivity to memory sub-timing parameters—tightening tRFC values improves stability on Samsung B-die memory modules but causes crashes on Micron E-die.

Profitability Calculation Framework

1. Incorporate pool fee structures beyond nominal percentages—some pools charge additional fees for low-difficulty share submissions or impose latency penalties above 200ms round-trip time.

2. Account for network difficulty adjustment windows: algorithms with 24-hour retargeting periods create volatility spikes that distort short-term profitability metrics.

3. Include exchange withdrawal fees and blockchain confirmation delays as cost components—Bitcoin Gold payouts incur 0.001 BTG fees plus 10-block confirmations averaging 120 minutes.

4. Factor in local electricity rate tiers—time-of-use billing plans can shift optimal mining windows by up to 8 hours daily without altering hardware configuration.

5. Model ASIC competition pressure: algorithms like SHA-256 and Scrypt show declining GPU profitability curves when new ASIC models enter production, even if hash price remains stable.

Common Questions

Q: Does overclocking memory always increase mining hashrate?Not universally. On KawPoW, increasing memory clock beyond 2200MHz on Radeon RX 6800 XT introduces timing violations that raise stale share rates by 7.3%, negating gains.

Q: Can I mine different algorithms simultaneously on one GPU?Current drivers prohibit concurrent kernel execution for memory-hard algorithms. Attempting dual-algorithm mining triggers watchdog timeouts and forces driver resets.

Q: Why does my RTX 3080 report higher hashrate on NBMiner than PhoenixMiner for Ergo?Divergent implementations of the Autolykos v2 memory access pattern—NBMiner uses optimized scatter-gather instructions while PhoenixMiner relies on legacy memory copy paths.

Q: Do PCIe lane configurations impact mining performance?Only for algorithms requiring frequent host-to-device transfers like RandomX. Running an RTX 4090 on x8 instead of x16 reduces RandomX throughput by 11.4% but shows no measurable difference on Ethash.