图11 展示了增加 inference-time computation 带来的优势。 图11:Inference-time Scaling 结果 SANA 在 GenEval 上的精度随采样的增加不断提高。其次,推理时间缩放使较小的 SANA 模型能够匹配甚至超过较大模型的准确性 (1.6B + 缩放优于 4.8B)。这些结果揭示了 scaling up infer
新的scaling law 正在浮现:算力周期性从 scaling 转移到 inference-time compute 对于GPT-4, Claude-3.5 水平的模型,我们推测要合成 1-10T 量级的高质量推理数据才能真正让模型大幅提升其推理能力,对应的成本大致需要 6-60 亿美金,这个在模型训练实验的算力中占的比例也是比较大的。 因此RL 范式下,scaling law ...
Prado, R. and West, M. (2010). Time Series: Modeling, Computation & In- ference. Chapman & Hall/CRC Press.Prado R, West M (2010) Time series: Modeling, computation and inference. London: Chapman & Hall/CRC Press, The Taylor Francis Group 17...
(iii) lead to speed-up in wall-clock time on modern hardware. asynchronous lookahead predictors learning-based algorithm to predict sparsity on the fly predicts a relevant subset of attention (heads) or MLP parameters in the next layer and only loads them for the computation hardware-efficient...
Generic secure computation techniques are mainstream for solving secure neural network inference problems. In the remainder of this section, we discuss existing works into three categories: (a) MPC-based protocols, (b) Fully Homomorphic Encryption (FHE)-based protocols, and (c) Trusted Execution Env...
Code Issues Pull requests Optimize layers structure of Keras model to reduce computation time keras inference-optimization Updated Jul 18, 2020 Python Rapternmn / PyTorch-Onnx-Tensorrt Star 80 Code Issues Pull requests A set of tool which would make your life easier with Tensorrt and Onn...
and most implementations are laid out that way as well, with one kind of computation done on the input data at a time in sequence. This doesn’t always lead to optimal performance, since it can be beneficial to do more calculations on values that have already been brought into the higher...
LLM-aware request routing to avoid KV cache recomputation costs Accelerated asynchronous data transfer between GPUs to reduce inference response time KV cache offloading across different memory hierarchies to increase system throughput Starting today, NVIDIA Dynamo is available f...
(DSC) mechanism: finds an optimal partitioning of the DNN model to be executed between IoT and edge to reduce the computation overhead (i.e., overall inference time); (2) reliable communication network switching (RCNS) mechanism: intelligently finds a suitable network to connect to either Wi...
Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching We develop a new form of reweighting (Wainwright et al., 2005) to leverage the relationship between Ising spin glasses and perfect matchings into a novel technique for the exact computation of MAP states in hit...