User profiles for Sanchit Misra
Sanchit MisraParallel Computing Lab, Intel Labs Verified email at intel.com Cited by 1971 |
Efficient architecture-aware acceleration of BWA-MEM for multicore systems
Innovations in Next-Generation Sequencing are enabling generation of DNA sequence
data at ever faster rates and at very low cost. For example, the Illumina NovaSeq 6000 …
data at ever faster rates and at very low cost. For example, the Illumina NovaSeq 6000 …
Distgnn: Scalable distributed training for large-scale graph neural networks
Full-batch training on Graph Neural Networks (GNN) to learn the structure of large graphs is
a critical problem that needs to scale to hundreds of compute nodes to be feasible. It is …
a critical problem that needs to scale to hundreds of compute nodes to be feasible. It is …
Benchmarking learned indexes
Recent advancements in learned index structures propose replacing existing index
structures, like B-Trees, with approximate learned models. In this work, we present a unified …
structures, like B-Trees, with approximate learned models. In this work, we present a unified …
Diffpack: A torsional diffusion model for autoregressive protein side-chain packing
Proteins play a critical role in carrying out biological functions, and their 3D structures are
essential in determining their functions. Accurately predicting the conformation of protein side-…
essential in determining their functions. Accurately predicting the conformation of protein side-…
Accelerating minimap2 for long-read sequencing applications on modern CPUs
Long-read sequencing is now routinely used at scale for genomics and transcriptomics
applications. Mapping long reads or a draft genome assembly to a reference sequence is often …
applications. Mapping long reads or a draft genome assembly to a reference sequence is often …
Lung cancer survival prediction using ensemble data mining on SEER data
We analyze the lung cancer data available from the SEER program with the aim of developing
accurate survival prediction models for lung cancer. Carefully designed preprocessing …
accurate survival prediction models for lung cancer. Carefully designed preprocessing …
The case for a learned sorting algorithm
Sorting is one of the most fundamental algorithms in Computer Science and a common
operation in databases not just for sorting query results but also as part of joins (ie, sort-merge-…
operation in databases not just for sorting query results but also as part of joins (ie, sort-merge-…
Accelerating sequence alignment to graphs
Aligning DNA sequences to an annotated reference is a key step for genotyping in biology.
Recent scientific studies have demonstrated improved inference by aligning reads to a …
Recent scientific studies have demonstrated improved inference by aligning reads to a …
A lung cancer outcome calculator using ensemble data mining on SEER data
We analyze the lung cancer data available from the SEER program with the aim of
developing accurate survival prediction models for lung cancer using data mining techniques. …
developing accurate survival prediction models for lung cancer using data mining techniques. …
Tensor processing primitives: A programming abstraction for efficiency and portability in deep learning workloads
During the past decade, novel Deep Learning (DL) algorithms/workloads and hardware
have been developed to tackle a wide range of problems. Despite the advances in workload/…
have been developed to tackle a wide range of problems. Despite the advances in workload/…