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Sanjay Chatterjee is listed as Engineering Manager at NVIDIA at NVIDIA, based in Santa Clara, California, United States. AeroLeads shows a work email signal at nvidia.com and a matched LinkedIn profile for Sanjay Chatterjee.
Sanjay Chatterjee previously worked as Engineering Manager at Nvidia and Research Scientist, Fusion Theory and Computation Group at General Atomics. Sanjay Chatterjee holds Phd, Computer Science from Rice University.
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AeroLeads found 1 current-domain work email signal for Sanjay Chatterjee. Compare company email patterns before reaching out.
At NVIDIA, we are building DGX Cloud, which offers cloud-based AI-as-a-service on optimized GPU accelerated hardware and software stacks. My team is responsible for the core compute software that schedules and runs scalable AI, Deep Learning and HPC multi-node workloads on GPU container runtime systems. Read more about it here: https://www.nvidia.com/en-us/data-center/dgx-cloud/Previously, I've worked as a research scientist and contributed to multiple DoE/DARPA funded research and advanced technology projects for exascale systems, specifically in areas of novel programming models, parallel languages, compilers, and runtime systems.My PhD dissertation titled "Runtime Systems for Extreme Scale Platforms" identified the critical role of programming models and scalable runtime systems to handle the challenges of exascale computing.Read more about it here: https://hdl.handle.net/1911/76173Over the course of my career, I have developed skills to design scalable high-performance computing systems involving diverse processor architectures. I have co-authored more than 15 journal, peer-reviewed conference and workshop papers, and presented more than 10 invited talks, posters and demos. Contributed to open-source projects and written programming model specification documents. Served as general chair, session chair and program committee member at multiple technical conferences and workshops, as well as mentored students at both senior and graduate level research projects.
Listed skills include Algorithms, C++, Embedded Systems, Linux, and 4 others.
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Santa Clara, CA, US
GPU Cloud Compute Software | Scalable Infrastructure for AI, Deep Learning and HPC Workloads | Scheduling Algorithms | Container Runtime Systems | KubernetesAt NVIDIA, we are building DGX Cloud, which offers cloud-based AI-as-a-service on optimized GPU accelerated hardware and software stacks. My team is responsible for the core compute software that.
San Diego, CA, US
Scaling Plasma Fusion HPC Applications on O(10^6) cores in preparation for Exascale Systems | Multi-scale Physics Simulations
Houston, TX, US
This work (funded by Intel Corporation and Sandia National Labs) explored Asynchronous Many Task (AMT) programming models to address software resiliency challenges associated with frequent hardware faults expected in future extreme scale systems. The Open Community Runtime (OCR) AMT programming model, based on the expression of explicit task dependencies.
Santa Clara, California, US
Worked on the DoE funded XStack Traleika Glacier project at Intel Federal which explored a revolutionary exascale-class machine software framework. The central thesis was this machine would need a self-adaptive distributed runtime layer to manage the large number of tasks, dynamically changing application and machine behaviors, and significant.
Santa Clara, California, US
Interned at Intel Labs on a project funded by the DARPA UHPC grant. Worked on a research team that was designing next generation parallel programming models and runtime systems that can efficiently scale HPC applications on Exascale systems. The summer was spent investigating methods to reduce the overheads of legacy programming systems by leveraging.
Redmond, Washington, US
Interned at Microsoft Research during my first summer after starting my PhD at Rice University. Worked with the Parallel Computing Platform group on the ConcRT runtime. ConcRT is concurrency runtime designed to scale applications using a task parallel programming model.
Santa Clara, CA, US
Developed various optimizations and features for NVIDIA’s runtime GPU compiler, CUDA compiler and CG compiler. Developed and maintained new features for supporting the latest ISA revisions. Implemented feature sets for 3 different ISA generations. Involved in design of the compiler intermediate representation. Handled performance tuning work for various.
US
Developed and maintained the parallelizing compiler frontend of PICO Express. Implemented algorithms for fast design space exploration. The tool takes algorithm descriptions expressed in terms of sequences of nested loops to map onto a highly optimized pipeline processor array (PPA) architecture. Implemented a new C++ frontend for PICO Express using the.
Kharagpur, West Bengal, IN
Development of software tools for CR16C/CRX processor on Linux platform.(Funded by National Semiconductor, USA – http://www.national.com/appinfo/compactrisc)The project was to develop and generate the complete tool set consisting of the Compiler, Assembler, Linker and Simulator for the CRX architecture, a 32 bit RISC processor from National Semiconductor..
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Kevin Koschoreck
Colleague at NvidiaRidgefield, Washington, United States, United States
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Sh Y
Colleague at NvidiaIstanbul, Istanbul, Türkiye, Turkey
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Carl Norum
Colleague at NvidiaSan Francisco Bay Area, United States, United States
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Alexander Kalinkin
Colleague at NvidiaRedmond, Washington, United States, United States
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Sing-Han Chen
Colleague at NvidiaTaipei City, Taipei City, Taiwan, Taiwan, Province Of China
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Yoel Sluzt
Colleague at NvidiaHarish, Haifa District, Israel, Israel
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Lior Granovsky
Colleague at NvidiaIsrael, Israel
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Eric Dawson
Colleague at NvidiaNew York, New York, United States, United States
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Eric Wilson
Colleague at NvidiaUnited States, United States
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Hafez Khamaisy
Colleague at NvidiaKfar Kana, North District, Israel, Israel
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Quick answers generated from the profile data available on this page.
Sanjay Chatterjee works for NVIDIA.
Sanjay Chatterjee is listed as Engineering Manager at NVIDIA at NVIDIA.
AeroLeads has found 1 work email signal at @nvidia.com for Sanjay Chatterjee at NVIDIA.
Sanjay Chatterjee is based in Santa Clara, California, United States while working with NVIDIA.
Sanjay Chatterjee has worked for Nvidia, General Atomics, Rice University, Intel Corporation, and Microsoft.
Sanjay Chatterjee's colleagues at NVIDIA include Kevin Koschoreck, Sh Y, Carl Norum, Alexander Kalinkin, and Sing-Han Chen.
You can use AeroLeads to view verified contact signals for Sanjay Chatterjee at NVIDIA, including work email, phone, and LinkedIn data when available.
Sanjay Chatterjee holds Phd, Computer Science from Rice University.
Sanjay Chatterjee is listed with skills including Algorithms, C++, Embedded Systems, Linux, Software Development, High Performance Computing, Opengl, and Compilers.
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