Results for “cpu”
12 skills
nvidia nemo-mbridge-perf-cpu-offloading
Configure and validate CPU offloading for Megatron Bridge training, including activation offloading and optimizer state offloading with HybridDeviceOptimizer.
2.2k · bundle
ichichuang pytorch-fsdp
Provides expert guidance on PyTorch Fully Sharded Data Parallel (FSDP) training, covering parameter sharding, mixed precision, CPU offloading, and FSDP2.
0 · bundle
orchestra-research llama-cpp
Run LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
10.4k · bundle
More results
orchestra-research gguf-quantization
Convert and quantize models to GGUF format for efficient CPU/GPU inference with llama.cpp, supporting 2-8 bit quantization and Apple Silicon acceleration.
10.4k · bundle
nvidia tao-run-on-lepton
Submit TAO jobs to Lepton managed GPU compute on DGX Cloud, with run/status/cancel interface and multi-node distributed training support.
2.2k · bundle
k-dense-ai optimize-for-gpu
GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, and other RAPIDS libraries for dramatic speedups on numerical, data, ML, graph, and simulation workloads.
30.2k · bundle
orchestra-research lambda-labs-gpu-cloud
Manage and use Lambda Labs GPU cloud instances for ML training and inference with SSH access, persistent filesystems, and multi-node clusters.
10.4k · bundle
orchestra-research nemo-curator
GPU-accelerated data curation for LLM training, supporting text, image, video, and audio with fuzzy deduplication, quality filtering, semantic deduplication, PII redaction, and NSFW detection.
10.4k · bundle
k-dense-ai cirq
Design, simulate, and run quantum circuits on Google Quantum AI hardware and partner backends using Cirq.
30.2k · bundle
qhjqhj00 flops
Evaluates computational throughput and real-time efficiency of embedded CPU and GPU platforms by measuring peak FLOPS via a matrix rotation kernel and assessing inference latency and power consumption on a robotic vision pipeline.
3
nvidia nemo-mbridge-perf-memory-tuning
Reduces peak GPU memory in Megatron Bridge training by applying expandable segments, parallelism resizing, activation recompute, and CPU offloading constraints.
2.2k · bundle
qhjqhj00 ray-data
Process large ML datasets in parallel across CPU or GPU clusters, with streaming execution, multi-format I/O, and integration with Ray Train, PyTorch, and TensorFlow for batch inference and preprocessing pipelines.
3 · bundle