A5103066009- Food Science and Nutritional Studies
- Software System Performance and Reliability
- Advanced Neural Network Applications
- Groundwater and Watershed Analysis
- Microencapsulation and Drying Processes
- Cloud Computing and Resource Management
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Water resources management and optimization
- Network Security and Intrusion Detection
- Advanced Chemical Sensor Technologies
- Advanced Image and Video Retrieval Techniques
- Explainable Artificial Intelligence (XAI)
- Neural Networks and Reservoir Computing
- Livestock Management and Performance Improvement
- Structural Engineering and Vibration Analysis
- Neural Networks and Applications
- Nuclear Materials and Properties
- Radiation Effects in Electronics
- Ferroelectric and Negative Capacitance Devices
- Engineering and Technology Innovations
- Domain Adaptation and Few-Shot Learning
- Metallurgical Processes and Thermodynamics
- Food Supply Chain Traceability
- Stochastic Gradient Optimization Techniques
Princeton Public Schools
2025
Georgia Institute of Technology
2024
International Institute of Information Technology
2024
Microsoft Research (United Kingdom)
2022
Chhattisgarh Kamdhenu Vishwavidyalaya
2015-2018
University of Agricultural Sciences, Bangalore
2001
Brookhaven National Laboratory
1981
Each LLM serving request goes through two phases. The first is prefill which processes the entire input prompt to produce one output token and second decode generates rest of tokens, one-at-a-time. Prefill iterations have high latency but saturate GPU compute due parallel processing prompt. In contrast, low also utilization because a iteration only single per request. This makes batching highly effective for decodes consequently overall throughput. However, multiple requests leads an...
Large Language Model (LLM) inference consists of two distinct phases - prefill phase which processes the input prompt and decode generates output tokens autoregressively. While effectively saturates GPU compute at small batch sizes, results in low utilization as it one token a time per request. The varying times also lead to imbalance across micro-batches when using pipeline parallelism, resulting further inefficiency due bubbles. We present SARATHI address these challenges. employs...
Logs serve as a critical tool for debugging and monitoring applications. However, gaining insights from unstructured logs is difficult. Hence, many log management analysis applications first parse into structured templates. In this paper, we train data-driven parser on our new Apache Spark dataset, the largest application dataset yet. We implement distributed online algorithm to accommodate large volume of data. also devise metric evaluation parsers when labeled data unavailable. show that...
Optimizing the deployment of Large language models (LLMs) is expensive today since it requires experimentally running an application workload against LLM implementation while exploring large configuration space formed by system knobs such as parallelization strategies, batching techniques, and scheduling policies. To address this challenge, we present Vidur - a large-scale, high-fidelity, easily-extensible simulation framework for inference performance. performance operators using...
Recommender systems utilize the times of yore experiences and preferences target customers as a basis to offer personalized recommendations for them well resolve information overloading hitch. Personalized recommendation methods are primarily classified into content-based approach collaborative filtering approach. Both approaches have their own advantages, drawbacks complementarities. Because conventional techniques don't consider contextual information, real factor why customer likes...
In many software applications, logs serve as the only interface between application and developer. However, navigating through of long-running applications is often challenging. Logs from previously successful runs can be leveraged to automatically identify errors provide users with that are relevant debugging process. We describe a privacy-preserving framework employed by Platform Service (PaaS) providers utilize user generated on platform while protecting potentially sensitive logged data....
Ice cream is a delicious and wholesome nutritious frozen food made by freezing pasteurized mix with agitation to incorporate air ensure uniformity of consistency. In present investigation, ginger-a natural herb was used as flavoring agent in ice cream. exposed temperature much lower than for freezing. Freezing rate therefore the time most fundamental properties during phenomena. The investigation taken up quantify variations thermal viz specific heat, conductivity, enthalpy various levels...
With the increase in scale of Deep Learning (DL) training workloads terms compute resources and time consumption, likelihood encountering in-training failures rises substantially, leading to lost work resource wastage. Such are typically offset by a checkpointing mechanism, which comes at cost storage network bandwidth overhead. State-of-the-art approaches involve lossy model compression mechanisms, induce tradeoff between resulting quality (accuracy) ratio. Delta is then used further reduce...
Dynamic simulation of the entire LMFBR plant is needed to determine after-heat dissipation capability via natural circulation. Models required accomplish this task are briefly described. The resulting computer code, Super System Code-Loop (SSC-L), then applied a loop-type fast reactor design illustrate system response for loss-of-electric-power event. Where possible, Clinch River Breeder Reactor Plant (CRBRP) specifications used. Entire performed up 1800 seconds transient time. Even with...
Lowering costs by driving high utilization across deep learning workloads is a crucial lever for cloud providers. We present Singularity, Microsoft's globally distributed scheduling service highly-efficient and reliable execution of training inference workloads. At the heart Singularity novel, workload-aware scheduler that can transparently preempt elastically scale to drive without impacting their correctness or performance, global fleet AI accelerators (e.g., GPUs, FPGAs). All jobs in are...
Cyclists have a high mortality and morbidity per mile travelled compared with car occupants, figure that is likely to increase if campaigns active travel are successful. The main thing preventing kids from cycling fear of injury. When children ride bicycles in near traffic, they engage complicated task combining motor skills cognitive skills. Bicycle safety education programs instruct on safe bicycle riding around addition helping them develop their handling But how much do bike initiatives...
Serving large language models (LLMs) in production can incur substantial costs, which has prompted recent advances inference system optimizations. Today, these systems are evaluated against conventional latency and throughput metrics (eg. TTFT, TBT, Normalised Latency TPOT). However, fail to fully capture the nuances of LLM inference, leading an incomplete assessment user-facing performance crucial for real-time applications such as chat translation. In this paper, we first identify pitfalls...
As large language models (LLMs) handle increasingly longer contexts, serving inference requests for context lengths in the range of millions tokens presents unique challenges. While existing techniques are effective training, they fail to address challenges inference, such as varying prefill and decode phases their associated latency constraints -- like Time First Token (TTFT) per Output (TPOT). Furthermore, no long-context solutions head-of-line blocking today. We present Medha, a system...
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTMultipurpose solvent extractorV. M. Bhuchar and A. K. AgrawalCite this: Anal. Chem. 1975, 47, 2, 360–363Publication Date (Print):February 1, 1975Publication History Published online1 May 2002Published inissue 1 February 1975https://pubs.acs.org/doi/10.1021/ac60352a026https://doi.org/10.1021/ac60352a026research-articleACS PublicationsRequest reuse permissionsArticle Views50Altmetric-Citations3LEARN ABOUT THESE METRICSArticle Views are the...
The present investigation was to determine the various physical characteristics of paneer whey with respect density, specific weight and electrical conductivity. These were determined considering three levels temperatures 20, 25 30oC at intervals 1, 2 3 h. highest values for density observed 1015.43 kg/m3 9.961 kN/m3 20oC respectively time it 1013.5 9.942 h respectively. conductivity 5.10 mS/cm 4.93 There is not much appreciable effect on variation time, whereas temperature had shown...
The present investigation was carried out to determine the various physical and electrical characteristics of skim milk with respect density, specific weight conductivity. These were determined considering three levels temperatures 25, 30 350C at intervals 0, 1, 2 3 h. highest values for density observed as1032.32 kg/m3 10.13 kN/m3at 250C respectively time it 1030.99 10.12 kN/m3 h respectively. conductivity 5.62mS/cm 5.54mS/cm There is not much appreciable effect variation on time, whereas...