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- Joined:
- Sep 20, 2022
- Messages:
- 17
I know there are like a thousand threads with this same issue but I cannot find a fix. I’ve looked through all the threads with the same issue and I cannot find an answer. I’ve tried all the solutions they have stated, and the problem still persists. Many of the threads I’ve looked in don’t have a single defined solution to this either, they all end abruptly with no further statements from any one party.
I have played it with 300 mods, gone through every single mod I have installed to see which one breaks it, played it with no mods, and I keep on crashing. Played with ultra graphics, potato graphics, sat afk for hours, played with 16 ai cars, and the same thing happens every time.
It isn’t a single action I perform that makes it crash either, it’s completely random. I can play for 10 minutes sometimes, maybe 30 minutes, maybe an hour. I’ve gone through and played for nearly 8 hours once. Between when the game worked fine, and when this issue started I changed nothing to the files, added or downloaded anything. I took a break from playing for about a week and when I came back this started happening.
The one thing I have not tried is underclocking my GPU, but I see no use for this since it runs average temps and has no problems with any other games I playVery much appreciated if anybody can find an actual permanent solution to this
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- Joined:
- Jul 25, 2020
- Messages:
- 203
What GPU do you have?
Are your drivers up to date? -
BeamNG Team
- Joined:
- Sep 16, 2020
- Messages:
- 1,253
Please submit your support ID; we’d like to look into your logs to identify the possible causes:
https://supportid.beamng.com
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- Joined:
- Sep 20, 2022
- Messages:
- 17
GTX 1080ti, been working wonders for years without issue. All drivers are up to dateID is 147426
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BeamNG Team
- Joined:
- Sep 16, 2020
- Messages:
- 1,253
Please follow these steps:
— Open your Userfolder (Launcher → Manage User Folder → Open in Explorer)
— Navigate one level up and find the folder with the latest version of the game
— Create a backup of this folder by renaming it, for example, `0.27 backup`
— The game will create a new folder -
- Joined:
- Sep 20, 2022
- Messages:
- 17
Ended up crashing a few hours in after doing this
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BeamNG Team
- Joined:
- Sep 16, 2020
- Messages:
- 1,253
Please submit your Support ID again
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- Joined:
- Jan 27, 2017
- Messages:
- 90
I have a GTX 1080 Ti and am getting crashes in Beamng too. coincidence? I’m not having issues with any other game, just beamng.
Go to BeamNG
r/BeamNG
BeamNG.drive is a realistic and immersive driving game, offering near-limitless possibilities and capable of doing just about anything!
BeamNG in-house soft-body physics engine simulates every component of a vehicle 2000 times per second in real time, resulting in realistic and high-fidelity dynamic behavior.
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FATAL ERROR: The GPU is not responding.
Question
This problem occured when I downloaded ReShade. I thought that uninstalling ReShade would solve the problem but it persisted. My drivers are up to date and I cleared cache. The error occurs in safe mode too. please help
2018.11.24:11:43:17.567: main Phoenix Miner 3.0c Windows/msvc — Release
2018.11.24:11:43:17.567: main Cmd line: -epool eu1.ethermine.org:4444 -ewal 0xf9e614e6903652f2bc8cec992b7632bddd208acc.RIG5 -epsw x
2018.11.24:11:43:17.567: main No CUDA driver found
2018.11.24:11:43:18.010: main Available GPUs for mining:
2018.11.24:11:43:18.010: main GPU1: Radeon RX 570 Series (pcie 1), OpenCL 2.0, 8 GB VRAM, 32 CUs
2018.11.24:11:43:18.010: main GPU2: Radeon RX 570 Series (pcie 2), OpenCL 2.0, 8 GB VRAM, 32 CUs
2018.11.24:11:43:18.010: main GPU3: Radeon RX 570 Series (pcie 3), OpenCL 2.0, 8 GB VRAM, 32 CUs
2018.11.24:11:43:18.010: main GPU4: Radeon RX 570 Series (pcie 4), OpenCL 2.0, 8 GB VRAM, 32 CUs
2018.11.24:11:43:18.010: main GPU5: Radeon RX 580 Series (pcie 5), OpenCL 2.0, 8 GB VRAM, 36 CUs
2018.11.24:11:43:18.032: main ADL library initialized
2018.11.24:11:43:18.316: main Listening for CDM remote manager at port 3333 in read-only mode
2018.11.24:11:43:18.316: main Eth: the pool list contains 2 pools
2018.11.24:11:43:18.316: main Eth: primary pool: eu1.ethermine.org:4444
2018.11.24:11:43:18.316: main Starting GPU mining
2018.11.24:11:43:18.316: main Matched GPU1 to ADL adapter index 24 (method 1)
2018.11.24:11:43:18.338: main GPU1: Using the X2 ODN API
2018.11.24:11:43:18.338: main GPU1: Created ADL monitor for adapter 24; overdrive version: 7
2018.11.24:11:43:18.338: main GPU1: using the blockchain beta driver
2018.11.24:11:43:18.339: main Matched GPU2 to ADL adapter index 6 (method 1)
2018.11.24:11:43:18.360: main GPU2: Using the X2 ODN API
2018.11.24:11:43:18.360: main GPU2: Created ADL monitor for adapter 6; overdrive version: 7
2018.11.24:11:43:18.360: main GPU2: using the blockchain beta driver
2018.11.24:11:43:18.360: main Matched GPU3 to ADL adapter index 18 (method 1)
2018.11.24:11:43:18.382: main GPU3: Using the X2 ODN API
2018.11.24:11:43:18.382: main GPU3: Created ADL monitor for adapter 18; overdrive version: 7
2018.11.24:11:43:18.382: main GPU3: using the blockchain beta driver
2018.11.24:11:43:18.382: main Matched GPU4 to ADL adapter index 12 (method 1)
2018.11.24:11:43:18.410: main GPU4: Using the X2 ODN API
2018.11.24:11:43:18.410: main GPU4: Created ADL monitor for adapter 12; overdrive version: 7
2018.11.24:11:43:18.410: main GPU4: using the blockchain beta driver
2018.11.24:11:43:18.410: main Matched GPU5 to ADL adapter index 0 (method 1)
2018.11.24:11:43:18.432: main GPU5: Using the X2 ODN API
2018.11.24:11:43:18.432: main GPU5: Created ADL monitor for adapter 0; overdrive version: 7
2018.11.24:11:43:18.432: main GPU5: using the blockchain beta driver
2018.11.24:11:43:18.433: wdog Starting watchdog thread
2018.11.24:11:43:18.433: main Eth: Connecting to ethash pool eu1.ethermine.org:4444 (proto: EthProxy)
2018.11.24:11:43:18.517: eths Eth: Connected to ethash pool eu1.ethermine.org:4444 (172.65.207.106)
2018.11.24:11:43:18.518: eths Eth: Send: {«id»:1,»jsonrpc»:»2.0″,»method»:»eth_submitLogin»,»worker»:»eth1.0″,»params»:[«0xf9e614e6903652f2bc8cec992b7632bddd208acc.RIG5″,»x»]}
2018.11.24:11:43:18.635: main GPU1: 39C 44%, GPU2: 36C 43%, GPU3: 35C 42%, GPU4: 35C 42%, GPU5: 32C 41%
2018.11.24:11:43:18.649: eths Eth: Received: {«id»:1,»jsonrpc»:»2.0″,»result»:true}
2018.11.24:11:43:18.649: eths Eth: Send: {«id»:5,»jsonrpc»:»2.0″,»method»:»eth_getWork»,»params»:[]}
2018.11.24:11:43:18.752: eths Eth: Received: {«id»:5,»jsonrpc»:»2.0″,»result»:[«0x52de906ff960d4517faa370b1642443a959c351d6bd64c9cf48026b19f10da4e»,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da4″]}
2018.11.24:11:43:18.752: eths Eth: New job #52de906f from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:18.753: GPU1 GPU1: Starting up… (0)
2018.11.24:11:43:18.753: GPU1 Eth: Generating light cache for epoch #225
2018.11.24:11:43:18.754: GPU2 GPU2: Starting up… (0)
2018.11.24:11:43:18.756: GPU3 GPU3: Starting up… (0)
2018.11.24:11:43:18.758: GPU4 GPU4: Starting up… (0)
2018.11.24:11:43:18.760: GPU5 GPU5: Starting up… (0)
2018.11.24:11:43:19.717: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0x218a2ff742497036aabac6bc6059ae3172eca5fb94ef1d273db72ca3d8cc3167″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da5″]}
2018.11.24:11:43:19.717: eths Eth: New job #218a2ff7 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:19.899: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0xaeb5b6309928248a8701b7b2c2f960efcdeeeffbbfe2eb3c0f4c9ea80a5dd757″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da5″]}
2018.11.24:11:43:19.899: eths Eth: New job #aeb5b630 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:22.099: GPU1 GPU1: Using new optimized OpenCL kernels (device name ‘Ellesmere’)
2018.11.24:11:43:22.099: GPU1 GPU1: Allocating DAG (2.77) GB; good for epoch up to #227
2018.11.24:11:43:22.099: GPU1 GPU1: Allocating light cache buffer (44.4) MB; good for epoch up to #227
2018.11.24:11:43:22.224: GPU1 GPU1: Generating DAG for epoch #225
2018.11.24:11:43:22.523: GPU2 GPU2: Using new optimized OpenCL kernels (device name ‘Ellesmere’)
2018.11.24:11:43:22.523: GPU2 GPU2: Allocating DAG (2.77) GB; good for epoch up to #227
2018.11.24:11:43:22.523: GPU2 GPU2: Allocating light cache buffer (44.4) MB; good for epoch up to #227
2018.11.24:11:43:22.644: GPU2 GPU2: Generating DAG for epoch #225
2018.11.24:11:43:22.963: GPU3 GPU3: Using new optimized OpenCL kernels (device name ‘Ellesmere’)
2018.11.24:11:43:22.963: GPU3 GPU3: Allocating DAG (2.77) GB; good for epoch up to #227
2018.11.24:11:43:22.963: GPU3 GPU3: Allocating light cache buffer (44.4) MB; good for epoch up to #227
2018.11.24:11:43:23.084: GPU3 GPU3: Generating DAG for epoch #225
2018.11.24:11:43:23.402: GPU4 GPU4: Using new optimized OpenCL kernels (device name ‘Ellesmere’)
2018.11.24:11:43:23.402: GPU4 GPU4: Allocating DAG (2.77) GB; good for epoch up to #227
2018.11.24:11:43:23.402: GPU4 GPU4: Allocating light cache buffer (44.4) MB; good for epoch up to #227
2018.11.24:11:43:23.493: main Eth speed: 0.000 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:23.493: main GPUs: 1: 0.000 MH/s (0) 2: 0.000 MH/s (0) 3: 0.000 MH/s (0) 4: 0.000 MH/s (0) 5: 0.000 MH/s (0)
2018.11.24:11:43:23.524: GPU4 GPU4: Generating DAG for epoch #225
2018.11.24:11:43:23.835: GPU5 GPU5: Using new optimized OpenCL kernels (device name ‘Ellesmere’)
2018.11.24:11:43:23.835: GPU5 GPU5: Allocating DAG (2.77) GB; good for epoch up to #227
2018.11.24:11:43:23.835: GPU5 GPU5: Allocating light cache buffer (44.4) MB; good for epoch up to #227
2018.11.24:11:43:23.905: GPU1 GPU1: DAG 25%
2018.11.24:11:43:23.959: GPU5 GPU5: Generating DAG for epoch #225
2018.11.24:11:43:24.267: GPU2 GPU2: DAG 25%
2018.11.24:11:43:24.737: GPU3 GPU3: DAG 25%
2018.11.24:11:43:25.154: GPU4 GPU4: DAG 25%
2018.11.24:11:43:25.415: GPU1 GPU1: DAG 50%
2018.11.24:11:43:25.539: GPU5 GPU5: DAG 31%
2018.11.24:11:43:26.082: GPU2 GPU2: DAG 56%
2018.11.24:11:43:26.601: GPU3 GPU3: DAG 56%
2018.11.24:11:43:26.918: GPU1 GPU1: DAG 75%
2018.11.24:11:43:26.992: GPU4 GPU4: DAG 56%
2018.11.24:11:43:27.272: GPU5 GPU5: DAG 69%
2018.11.24:11:43:27.896: GPU2 GPU2: DAG 88%
2018.11.24:11:43:28.422: GPU1 GPU1: DAG 100%
2018.11.24:11:43:28.422: GPU1 GPU1: DAG generated in 6.2 s (455.7 MB/s)
2018.11.24:11:43:28.422: GPU1 GPU1: no gt value specified, switching to auto-tune
2018.11.24:11:43:28.422: GPU1 GPU1: starting auto-tune process
2018.11.24:11:43:28.465: GPU3 GPU3: DAG 88%
2018.11.24:11:43:28.518: eths Eth: Send: {«id»:5,»jsonrpc»:»2.0″,»method»:»eth_getWork»,»params»:[]}
2018.11.24:11:43:28.540: main Eth speed: 0.000 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:28.540: main GPUs: 1: 0.000 MH/s (0) 2: 0.000 MH/s (0) 3: 0.000 MH/s (0) 4: 0.000 MH/s (0) 5: 0.000 MH/s (0)
2018.11.24:11:43:28.622: GPU2 GPU2: DAG generated in 6.0 s (472.4 MB/s)
2018.11.24:11:43:28.623: GPU2 GPU2: no gt value specified, switching to auto-tune
2018.11.24:11:43:28.623: GPU2 GPU2: starting auto-tune process
2018.11.24:11:43:28.623: eths Eth: Received: {«id»:5,»jsonrpc»:»2.0″,»result»:[«0xaeb5b6309928248a8701b7b2c2f960efcdeeeffbbfe2eb3c0f4c9ea80a5dd757″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da5″]}
2018.11.24:11:43:28.715: GPU5 GPU5: DAG generated in 4.8 s (593.8 MB/s)
2018.11.24:11:43:28.716: GPU5 GPU5: no gt value specified, switching to auto-tune
2018.11.24:11:43:28.716: GPU5 GPU5: starting auto-tune process
2018.11.24:11:43:28.830: GPU4 GPU4: DAG 88%
2018.11.24:11:43:29.210: GPU3 GPU3: DAG generated in 6.1 s (461.0 MB/s)
2018.11.24:11:43:29.211: GPU3 GPU3: no gt value specified, switching to auto-tune
2018.11.24:11:43:29.211: GPU3 GPU3: starting auto-tune process
2018.11.24:11:43:29.565: GPU4 GPU4: DAG generated in 6.0 s (467.5 MB/s)
2018.11.24:11:43:29.566: GPU4 GPU4: no gt value specified, switching to auto-tune
2018.11.24:11:43:29.566: GPU4 GPU4: starting auto-tune process
2018.11.24:11:43:29.828: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0x7cce1e60f4fce409803a34778078eea765c6907ada2dacd414fdd4b2ece71065″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da5″]}
2018.11.24:11:43:29.828: eths Eth: New job #7cce1e60 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:33.087: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0x3f58698557a61538306afe1fa4d916198cd8378c2f009f7e97ee3d6c653a65e8″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da6″]}
2018.11.24:11:43:33.087: eths Eth: New job #3f586985 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:33.151: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0x5a1761730285cc0b935b8df0568b84e9e372dc78c92873d6a039860863af24ac»,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da6″]}
2018.11.24:11:43:33.151: eths Eth: New job #5a176173 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:33.589: main Eth speed: 115.595 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:33.589: main GPUs: 1: 22.370 MH/s (0) 2: 22.915 MH/s (0) 3: 22.716 MH/s (0) 4: 20.660 MH/s (0) 5: 26.934 MH/s (0)
2018.11.24:11:43:38.519: eths Eth: Send: {«id»:5,»jsonrpc»:»2.0″,»method»:»eth_getWork»,»params»:[]}
2018.11.24:11:43:38.519: eths Eth: Send: {«id»:6,»jsonrpc»:»2.0″,»method»:»eth_submitHashrate»,»params»:[«0x6e3d56b»,»0x0fa016a863f9317f2cfe5f68173090304342d5a24cd86788dd684538c76f95e8″]}
2018.11.24:11:43:38.625: eths Eth: Received: {«id»:5,»jsonrpc»:»2.0″,»result»:[«0x5a1761730285cc0b935b8df0568b84e9e372dc78c92873d6a039860863af24ac»,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da6″]}
2018.11.24:11:43:38.625: eths Eth: Received: {«id»:6,»jsonrpc»:»2.0″,»result»:true}
2018.11.24:11:43:38.637: main Eth speed: 117.496 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:38.637: main GPUs: 1: 22.480 MH/s (0) 2: 22.939 MH/s (0) 3: 22.747 MH/s (0) 4: 22.780 MH/s (0) 5: 26.550 MH/s (0)
2018.11.24:11:43:43.099: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0x3f01b1160fcab254dd65cdb061d8ec1538cc6e880ed8f81e975ef971021fed26″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da6″]}
2018.11.24:11:43:43.099: eths Eth: New job #3f01b116 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:43.681: main Eth speed: 105.314 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:43.681: main GPUs: 1: 19.831 MH/s (0) 2: 20.085 MH/s (0) 3: 20.102 MH/s (0) 4: 20.563 MH/s (0) 5: 24.734 MH/s (0)
2018.11.24:11:43:46.505: main GPU1: 49C 48%, GPU2: 44C 46%, GPU3: 41C 46%, GPU4: 45C 46%, GPU5: 47C 47%
2018.11.24:11:43:48.520: eths Eth: Send: {«id»:5,»jsonrpc»:»2.0″,»method»:»eth_getWork»,»params»:[]}
2018.11.24:11:43:48.624: eths Eth: Received: {«id»:5,»jsonrpc»:»2.0″,»result»:[«0x3f01b1160fcab254dd65cdb061d8ec1538cc6e880ed8f81e975ef971021fed26″,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da6″]}
2018.11.24:11:43:48.725: main Eth speed: 80.805 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:48.725: main GPUs: 1: 19.061 MH/s (0) 2: 19.017 MH/s (0) 3: 0.000 MH/s (0) 4: 18.636 MH/s (0) 5: 24.091 MH/s (0)
2018.11.24:11:43:53.135: eths Eth: Received: {«id»:0,»jsonrpc»:»2.0″,»result»:[«0xfd93ded7a78291d163732a7e5bca2e4210abea881e087441e3332860331ee92e»,»0x7424fbb6ab0049bfa974e06597777d2b71283d3b339685eaa072c77c2ea960ff»,»0x0112e0be826d694b2e62d01511f12a6061fbaec8bc02357593e70e52ba»,»0x672da6″]}
2018.11.24:11:43:53.135: eths Eth: New job #fd93ded7 from eu1.ethermine.org:4444; diff: 4000MH
2018.11.24:11:43:53.771: main Eth speed: 91.041 MH/s, shares: 0/0/0, time: 0:00
2018.11.24:11:43:53.771: main GPUs: 1: 21.487 MH/s (0) 2: 21.643 MH/s (0) 3: 0.000 MH/s (0) 4: 21.417 MH/s (0) 5: 26.494 MH/s (0)
2018.11.24:11:43:56.383: unkn Quitting…
2018.11.24:11:43:56.383: unkn GPU1 auto-tune process aborted
2018.11.24:11:43:56.682: unkn GPU2 auto-tune process aborted
2018.11.24:11:43:57.147: unkn GPU3 auto-tune process aborted
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As a data scientist or software engineer you may encounter an issue where your GPU stops responding while performing calculations This can be a frustrating experience especially when you are working on a project with a tight deadline In this article we will discuss the reasons why this error occurs and provide you with the steps you can take to resolve it
As a data scientist or software engineer, you may encounter an issue where your GPU stops responding while performing calculations. This can be a frustrating experience, especially when you are working on a project with a tight deadline. In this article, we will discuss the reasons why this error occurs and provide you with the steps you can take to resolve it.
What Causes the “Stopped Responding” Error?
The “stopped responding” error occurs when your GPU driver stops responding to commands from the operating system. This can happen due to several reasons, including:
-
Overheating: When the GPU temperature exceeds its limit, it may stop responding to commands. This is a safety mechanism that prevents the GPU from getting damaged due to overheating.
-
Outdated Drivers: If your GPU drivers are outdated, they may not be able to handle the workload, leading to the “stopped responding” error.
-
Insufficient Power Supply: If your GPU is not receiving enough power, it may stop responding to commands.
-
Hardware Issues: In some cases, hardware issues such as a faulty GPU or a damaged PCIe slot can also lead to the “stopped responding” error.
How to Resolve the “Stopped Responding” Error
If you encounter the “stopped responding” error while performing calculations on your GPU, here are the steps you can take to resolve it:
Step 1: Check the GPU Temperature
The first step is to ensure that your GPU is not overheating. To check the GPU temperature, you can use software such as GPU-Z or MSI Afterburner. If the temperature is above the recommended limit, you can try the following solutions:
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Increase Fan Speed: You can increase the fan speed of your GPU using software such as MSI Afterburner. This will help dissipate the heat more effectively.
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Clean Your GPU: Over time, dust can accumulate on your GPU’s heatsink and fan, reducing their effectiveness. You can use compressed air to clean your GPU and ensure that it is running at optimal temperatures.
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Improve Airflow: If your GPU is not receiving enough airflow, you can improve it by ensuring that your computer case has sufficient fans and that they are positioned correctly.
Step 2: Update Your GPU Drivers
If your GPU drivers are outdated, you can update them to the latest version. To do this, you can visit the website of your GPU manufacturer and download the latest drivers for your GPU. Alternatively, you can use software such as Driver Booster to automatically update your drivers.
Step 3: Ensure Sufficient Power Supply
If your GPU is not receiving sufficient power, you can try the following solutions:
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Check Power Supply Unit (PSU): Ensure that your PSU is providing enough power to your GPU. You can use software such as HWMonitor to check the voltage and current readings of your PSU.
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Use a Dedicated Power Connector: Some GPUs require a dedicated power connector to function properly. Ensure that your GPU is connected to the correct power connector.
Step 4: Check for Hardware Issues
If none of the above solutions work, it is possible that your GPU or PCIe slot is faulty. In this case, you can try the following solutions:
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Test Your GPU on Another Computer: Test your GPU on another computer to determine if it is faulty.
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Check the PCIe Slot: Ensure that the PCIe slot is not damaged and that the GPU is properly seated.
Conclusion
In conclusion, the “stopped responding” error when calculating on your GPU can be a frustrating experience. However, by following the steps outlined in this article, you can resolve the issue and get back to work. Remember to check the GPU temperature, update your drivers, ensure sufficient power supply, and check for hardware issues. These steps will help you diagnose and resolve the issue, ensuring that your GPU is running at optimal performance.
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