How Awesome Miner Logs Help Analyse Hashrate Instability Over Time

Scrutinize the JSON-structured event trails generated by your extraction software. These chronicles capture GPU power draw, core clock deviations, and share submission timestamps with millisecond precision. A consistent drop in accepted solutions, correlated with a 12% spike in hardware errors between 14:00 and 16:00 UTC, points directly to thermal throttling. Cross-reference these entries with your pool’s dashboard to confirm the pattern.

Focus on event IDs 1323 and 0x8007, which signal hardware faults and rejected computational work. A sequence of these codes preceding a 15 MH/s drop is a definitive indicator. Isolate periods where fan speeds reported in the operational dossiers fluctuate between 80% and 100% while core temperatures exceed 84°C. This thermal stress forces the hardware to reduce its clock speeds, protecting the silicon at the cost of delivered power.

Implement a systematic review by exporting these data points to a time-series database. Plot core frequency against temperature and rejected work units. The visual correlation will expose instability triggers more clearly than a manual log review. This method transforms raw, textual records into an actionable diagnostic chart, enabling preemptive configuration adjustments to maintain consistent output.

Awesome Miner Logs for Hashrate Instability Analysis

Immediately configure your application to record events at a ‘Verbose’ or ‘Debug’ level; standard settings frequently omit critical diagnostic information.

Scrutinize entries for GPU core clock, memory clock, and power draw fluctuations. A stable hashing output requires consistent hardware performance. Correlate any performance dips with thermal throttling warnings, typically logged as ‘Temperature Limit’ or ‘Thermal Paste’.

Examine the records for rejected shares and connection latency to the mining pool. A high ‘Stale’ or ‘Invalid’ share count, coupled with ping times exceeding 500ms, directly points to network or pool-side issues as the primary cause of erratic output.

Cross-reference timestamps of hardware errors with driver messages. Look for Windows Event Viewer entries related to ‘Display driver nvlddmkm stopped responding’ or similar, which indicate underlying system instability affecting computational consistency.

Isolate periods of algorithm switching. Automated profit-switching features can create the appearance of volatility; check the log for entries like ‘Switching from Ethash to KawPow’ to distinguish intended behavior from genuine malfunction.

Aggregate this data into a time-series chart. Plotting computational power, temperature, and share acceptance rate on a single graph will visually pinpoint the exact moment a problem began and its potential triggers.

Locating and Interpreting Hashrate Fluctuation Patterns in Log Files

Begin by isolating entries containing the keywords “accepted,” “diff,” and “GPU” within the primary operational record of your Awesome Miner setup. These lines provide the core data points for computational performance.

Establish a baseline for your hardware by calculating the average submitted share count per minute during a stable 6-hour window. A deviation of more than 15% from this baseline indicates a significant performance event requiring investigation.

• Pattern: Cyclical Dips (Sawtooth Waveform)
• Log Evidence: Repeated “GPU X, temp: 78°C” entries followed by a clock speed reduction and a subsequent “accepted” slowdown.
• Interpretation: Active thermal protection. The graphics card is throttling to prevent overheating.
• Action: Improve chassis airflow, repaste the GPU thermal compound, or increase fan curve aggressiveness.

• Pattern: Sharp, Isolated Drop to Zero
• Log Evidence: A sequence of “GPU X – error,” “connection lost,” or “job not found,” followed by a 30-60 second pause and a “new job started” message.
• Interpretation: Pool connection failure or a software-level crash on the specific device.
• Action: Verify network stability, check for conflicting processes, and update the device driver to the latest stable version.

• Pattern: Gradual Performance Degradation
• Log Evidence: The “accepted” interval slowly increases from 45 seconds to 90+ seconds over several hours, with a corresponding rise in “hardware errors.”
• Interpretation: The card is becoming unstable, often due to an overclock that is too aggressive for its sustained operating temperature.
• Action: Reduce the core clock and memory clock offsets incrementally until the hardware error count remains near zero.

Correlate these computational patterns with system events. Cross-reference timestamps with Windows Event Viewer for critical errors or driver failures. A memory management blue screen occurring simultaneously with a performance drop confirms a system-level instability, not a configuration issue within the management software.

Correlating Pool Rejections and Hardware Errors with Performance Dips

Immediately cross-reference the timestamps of high rejection rates from your pool’s dashboard with entries in the excavator’s event record. A direct correlation points to a connectivity or configuration problem, not a local machine fault.

Interpreting Stale and Invalid Share Reports

Stale share spikes, indicated by messages containing ‘stale’ or obsolete block data, reveal network latency. Investigate your connection’s ping time to the pool server; a delay over 100ms often causes this. Invalid shares, flagged as ‘invalid’ or ‘job not found’, typically result from an overclocked graphics processor or memory. Reduce the core clock by 25 MHz and the memory clock by 50 MHz, then retest for stability.

Decoding Device Failure Indicators

Scrutinize the event feed for entries like ‘GPU X – GPU crash detected’ or ‘HW error 0’. These hardware faults directly cause computational output to collapse. A consistent pattern of such errors for a specific processing unit demands an immediate reduction in its power limit or operating frequency. For example, a card generating multiple hardware faults per hour should have its power target lowered by 10%.

Persistent issues, even after underclocking, may indicate failing thermal paste or dust-clogged heatsinks. Monitor the GPU hotspot temperature; a differential exceeding 30°C to the core temperature confirms inadequate cooling and necessitates physical maintenance.

FAQ:

What is the main purpose of Awesome Miner’s log files for a mining rig operator?

The primary use of Awesome Miner’s logs is to diagnose why your mining performance fluctuates. The software continuously records data about your hardware, the mining pool connection, and the algorithms. When your hashrate drops or becomes unstable, these log files are the first place to check. They contain a history of events, errors, and performance metrics that can help you pinpoint the root cause, whether it’s a hardware failure, an overheating GPU, a software crash, or connectivity problems with the mining pool.

Which specific log entries should I look for first when my reported hashrate on the pool is lower than my local hashrate?

Focus on entries related to pool communication and share submission. Look for lines containing “share accepted” and note the frequency. A long gap between these messages indicates a problem. Also, search for keywords like “rejected”, “stale”, or “invalid” shares. A high number of these directly reduces your earnings. Check for network timeouts or connection reset messages, which show the miner lost contact with the pool. High reject rates often point to an unstable internet connection or an overclock that is too aggressive, causing the GPU to produce incorrect calculations.

My log shows a lot of “GPU X: Temperature Y” entries. How can I use this to fix instability?

Temperature logs are critical for hardware stability. Organize these entries by GPU and time to see the temperature trend. If a specific GPU consistently runs 10-15°C hotter than others, its cooling might be insufficient. Look for thermal throttling events, where the clock speed drops to reduce heat. This causes a direct hashrate drop. The solution is to improve airflow in the rig case, clean dust from the GPU heatsink and fans, or adjust the fan curve in your mining software or BIOS to be more aggressive. Reapplying thermal paste on a consistently hot GPU can also be a effective long-term fix.

Can Awesome Miner logs help me identify a failing GPU before it completely stops working?

Yes, the logs can show early warning signs of GPU failure. Watch for a pattern of specific errors linked to one GPU. These can include DirectX errors, OpenCL failures, or driver crash and recovery messages that always mention the same GPU device ID. You might also see a gradual increase in hardware error counts for that card. Another sign is a progressive decline in its individual hashrate while temperatures remain normal, suggesting the card can no longer maintain stable compute operations. Identifying these patterns early allows you to remove the card for testing or repair, preventing it from crashing the entire mining operation.

I see “Algorithm ‘X’ crashed” messages followed by a miner restart. What does this mean and how can I stop it?

An algorithm crash means the specific mining software for that cryptocurrency algorithm stopped working unexpectedly. The log should have an entry just before the crash that gives a clue. Common causes are incorrect overclocking settings, insufficient virtual memory, or a problem with the miner file itself. To resolve this, first reset your GPU overclocks to default values to rule that out. Increase your system’s virtual memory (page file) to at least 1.5 times your total GPU memory. If the problem continues, check the Awesome Miner log for the exact miner it was using and try updating or reinstalling that specific miner plugin from the Tools menu.

My Awesome Miner shows frequent hashrate drops and spikes. Which specific log files should I look at first, and what patterns indicate a hardware issue versus a pool connection problem?

Start with the `miner.log` file, which records detailed data from each mining device. For hardware-related instability, search for lines containing “GPU” or device IDs alongside words like “speed,” “invalid,” or “rejected.” A consistent pattern of hardware errors or a gradual decline in reported speed for a specific card points to an overclocking issue, insufficient power, or failing hardware. For pool problems, focus on entries with “pool,” “stratum,” or the pool’s address. Frequent “disconnect” and “reconnect” messages, or “share rejected” errors that affect all your devices simultaneously, typically indicate network latency, an unstable pool server, or internet connectivity problems. Correlate the timestamps of the hashrate drops in the main interface with these log events to pinpoint the exact cause.

I found a lot of “share above target” errors in my logs. What does this mean, and how can I fix it?

A “share above target” error means your miner submitted a share that the pool considered invalid because its calculated value exceeded the difficulty target. This is often caused by hardware instability. An overclocked GPU that isn’t completely stable can produce these incorrect calculations. The first step is to reduce the core and memory clock speeds on your GPU or increase its power limit. Using a more aggressive fan curve to improve cooling can also help, as overheating can lead to similar errors. If the problem continues after adjusting your overclocks, test the specific GPU with a mining-specific stress test or benchmark to rule out a deeper hardware fault.

Reviews

NovaSpark

My rigs used to spike and crash daily. I wasted weeks guessing until I started dissecting the Awesome Miner logs properly. Stop looking at the dashboard averages. The real story is in the detailed event logs and the miner-specific files. Cross-reference timestamps from the AM service log with your miner’s console output. You’ll spot the exact moment a GPU throws a share error or the DAG fails to regenerate. That specific error code is your target, not the generic “instability” warning. This method cut my rejects by 70%. The logs tell you everything; you just have to stop skimming and start reading the evidence.

James Wilson

These logs are gold! My rig was acting wild, now I see every little wobble. This is the clarity we needed. No more guessing games, just fixing things. Finally, real control over our earnings!

David Clark

So these logs are supposed to reveal the hashrate gremlins? Let’s see the raw data, not another generic guide. Proof is in the timestamps and reject rates, not theories. Show me the money.

Charlotte

My rig’s been throwing a fit for weeks. The numbers would dip and spike like a bad heart rate monitor. I’d stare at the screen, muttering the kind of sweet nothings only a motherboard could love. Then I got serious about the logs. Not just a glance, but a real, slow read. Those text files are a confession booth. They tell you everything: which worker got lazy, when a share was rejected, if the pool connection got flaky. It’s not glamorous work. It’s like being a digital plumber, unclogging the pipes of my own frustration. But seeing a flat line on the graph after fixing a single, tiny misconfiguration? That’s the joke, and the payout is the punchline.

Olivia Johnson

My logs show these quiet pauses between the surges. Just brief, silent gaps in the numbers. Does your miner also hesitate like this, as if gathering its thoughts before speaking? What do you make of these gentle, rhythmic lulls?

Isabella Brown

Anyone else find their logs look like a dramatic novel? My rig’s plot twists are more frequent than my morning coffee breaks.