Search Results - "Srivastava, Prakalp"

Compilers for Portable Programming of Heterogeneous Parallel & Approximate Computing Systems by Srivastava, Prakalp

“…Programming heterogeneous systems such as the System-on-chip (SoC) processors in modern mobile devices can be extremely complex because a single system may…”
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An Energy-Efficient Programmable Mixed-Signal Accelerator for Machine Learning Algorithms by Kang, Mingu, Srivastava, Prakalp, Adve, Vikram, Kim, Nam Sung, Shanbhag, Naresh R.

“…We propose PROMISE, the first end-to-end design of a PROgrammable MIxed-Signal accElerator from Instruction Set Architecture to high-level language compiler…”
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PROMISE: An End-to-End Design of a Programmable Mixed-Signal Accelerator for Machine-Learning Algorithms by Srivastava, Prakalp, Kang, Mingu, Gonugondla, Sujan K., Lim, Sungmin, Choi, Jungwook, Adve, Vikram, Kim, Nam Sung, Shanbhag, Naresh

“…Analog/mixed-signal machine learning (ML) accelerators exploit the unique computing capability of analog/mixed-signal circuits and inherent error tolerance of…”
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Stash: Have your scratchpad and cache it too by Komuravelli, Rakesh, Sinclair, Matthew D., Alsop, Johnathan, Huzaifa, Muhammad, Kotsifakou, Maria, Srivastava, Prakalp, Adve, Sarita V., Adve, Vikram S.

“…Heterogeneous systems employ specialization for energy efficiency. Since data movement is expected to be a dominant consumer of energy, these systems employ…”
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POSTER - hVISC: A portable abstraction for heterogeneous parallel systems by Srivastava, Prakalp, Kotsifakou, Maria, Sinclair, Matthew D., Komuravelli, Rakesh, Adve, Vikram, Adve, Sarita

“…Programming heterogeneous parallel systems can be extremely complex because a single system may include multiple different parallelism models, instruction…”
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Relax: Composable Abstractions for End-to-End Dynamic Machine Learning by Lai, Ruihang, Shao, Junru, Feng, Siyuan, Lyubomirsky, Steven S, Hou, Bohan, Lin, Wuwei, Ye, Zihao, Jin, Hongyi, Jin, Yuchen, Liu, Jiawei, Jin, Lesheng, Cai, Yaxing, Jiang, Ziheng, Wu, Yong, Park, Sunghyun, Srivastava, Prakalp, Roesch, Jared G, Mowry, Todd C, Chen, Tianqi

“…Dynamic shape computations have become critical in modern machine learning workloads, especially in emerging large language models. The success of these models…”
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HPVM: A Portable Virtual Instruction Set for Heterogeneous Parallel Systems by Srivastava, Prakalp, Kotsifakou, Maria, Adve, Vikram

“…We describe a programming abstraction for heterogeneous parallel hardware, designed to capture a wide range of popular parallel hardware, including GPUs,…”
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A hardware architecture to deploy complex multiprocessor scheduling algorithms by Mancuso, Renato, Srivastava, Prakalp, Deming Chen, Caccamo, Marco

“…An increasing demand for high-performance systems has been observed in the domain of both general purpose and real-time systems, pushing the industry towards a…”
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