NVIDIA Tesla P40 · 24GB VRAM

ການຮຽນຮູ້ຂອງເຄື່ອງຈັກ GPU VPS

ເພີ່ມຄວາມໄວໃນການຮຽນຮູ້ຂອງເຄື່ອງຈັກດ້ວຍການຝຶກອົບຮົມແລະຜົນໄດ້ຮັບທີ່ໃຊ້ GPU. RAPIDS, XGBoost GPU, ແລະ scikit-learn ຢູ່ໃນຮາດແວ NVIDIA ທີ່ອຸທິດຕົນ.

ຕິດຕັ້ງម៉ាស៊ីនបម្រើ GPU ຕົວເລືອກ GPU ທັງໝົດ

$ pip install cuml-cu12 xgboost cudf-cu12
# ແລ່ນຢູ່ເທິງ NVIDIA Tesla P40 (24GB)
ພ້ອມແລ້ວ _

ຫຍັງຄື {ຊື່} ຢູ່ໃນ GPU VPS?

ການຮຽນຮູ້ຂອງເຄື່ອງຈັກທີ່ເພີ່ມຄວາມໄວ GPU ໃຊ້ NVIDIA CUDA ເພື່ອເພີ່ມຄວາມໄວໃນການຝຶກອົບຮົມແລະຄາດຄະເນ ສຳ ລັບ algorithms ML ແບບເກົ່າ. RAPIDS ແລະ XGBoost GPU ສາມາດສົ່ງຄວາມໄວ 10-100x ກ່ວາການຈັດຕັ້ງປະຕິບັດ CPU ເທົ່ານັ້ນ.

ເຮັດຫຍັງ {ຊື່} ຢູ່ໃນ VPS.org GPU

RAPIDS cuML

ເພີ່ມຄວາມໄວ GPU-speeded scikit-learn algorithms ທີ່ເຂົ້າກັນໄດ້

GPU XGBoost

ຝຶກອົບຮົມແບບຟອມເພີ່ມຄວາມໄວຂອງການປ່ຽນສີໃນ GPU 10x ໄວຂຶ້ນ.

cuDF & cuPy

pandas ແລະ numpy ຖືກເພີ່ມຄວາມໄວໂດຍ GPU ເພື່ອການປະມວນຜົນຂໍ້ມູນກ່ອນໜ້ານີ້.

GPU ສຸດທ້າຍເຖິງສຸດທ້າຍ

ຮັກສາ ML pipeline ຂອງທ່ານທັງ ໝົດ ຢູ່ໃນ GPU ເພື່ອຄວາມໄວສູງສຸດ.

ຕົວຢ່າງການໃຊ້ທີ່ນິຍົມ {ຊື່}

ການຈັດປະເພດ ແລະ ການຖອນຕົວ

ເຕັກນິກວິສະວະກໍາທີ່ມີລັກສະນະຕາມຂະໜາດ

ການຄາດຄະເນເວລາຈິງ

ຂະບວນການຈັດຕັ້ງຖານຂໍ້ມູນໃຫຍ່

ສາຍສົ່ງ AutoML

ແບບແບບຕົວແບບ

ຕິດຕັ້ງម៉ាស៊ីនបម្រើ GPU

ຄຸນສົມບັດຂອງ GPU

GPUNVIDIA Tesla P40

VRAM24 GB GDDR5X

ពណ៌ CUDA3,840

FP32 12 TFLOPS

INT847 TOPS

ຄວາມຈຳສີຂາວ346 GB/s

ສະຖາປັດຕະຍະກໍາPascal (GP102)

ຜ່ານPCIe ແບບບໍ່ມີໂລຫະ

ຄໍາຖາມທີ່ຖາມເລື້ອຍໆ

What is Machine Learning on a GPU VPS?

Machine Learning on a GPU VPS is a CUDA-accelerated deployment. Machine Learning is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Machine Learning.

How do I set up Machine Learning on a GPU VPS?

Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install cuml-cu12 xgboost cudf-cu12. Your Machine Learning environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Machine Learning?

Our GPU VPS ships with 24 GB GDDR5X VRAM on the NVIDIA Tesla P40, which is sufficient for most Machine Learning workloads. Multi-GPU configurations are available on request.

Is Machine Learning GPU VPS billed hourly or monthly?

GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.

Can I run other tools alongside Machine Learning?

Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside Machine Learning.

Do I get full root on the Machine Learning GPU VPS?

Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Machine Learning however you need.

Which CUDA version is installed for Machine Learning?

GPU VPSs ship with a recent CUDA runtime and the matching NVIDIA driver pre-installed. You can pin or upgrade CUDA versions as required by your Machine Learning workload.

Does my Machine Learning GPU VPS persist between sessions?

Yes — your Machine Learning GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.

Where should I store data for my Machine Learning workload?

Keep working data on the VPS SSD for fast access during Machine Learning runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.

Can I scale my Machine Learning GPU VPS later?

Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your Machine Learning install carries over.

Are backups available for my GPU VPS?

Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long Machine Learning training runs where you want a checkpointable server state.

Is there a money-back guarantee on the GPU VPS?

Yes — 30-day money-back guarantee on every plan including GPU. Try Machine Learning on a GPU VPS risk-free.