37 citations · 71 across the 7 of their papers we have counts for
7 papers
Kernel Looping: Eliminating Synchronization Boundaries for Peak Inference Performance
David Koeplinger, Darshan Gandhi, Pushkar Nandkar +9
Token generation speed is critical to power the next wave of AI inference applications. GPUs significantly underperform during token generation due to synchronization overheads at…
SambaNova SN40L: Scaling the AI Memory Wall with Dataflow and Composition of Experts
Raghu Prabhakar, Ram Sivaramakrishnan, Darshan Gandhi +27
Monolithic large language models (LLMs) like GPT-4 have paved the way for modern generative AI applications. Training, serving, and maintaining monolithic LLMs at scale, however, r…
Training Large Language Models Efficiently with Sparsity and Dataflow
Venkat Srinivasan, Darshan Gandhi, Urmish Thakker +1
Large foundation language models have shown their versatility in being able to be adapted to perform a wide variety of downstream tasks, such as text generation, sentiment analysis…
Revet: A Language and Compiler for Dataflow Threads
Alexander Rucker, Shiv Sundram, Coleman Smith +4
Spatial dataflow architectures such as reconfigurable dataflow accelerators (RDA) can provide much higher performance and efficiency than CPUs and GPUs. In particular, vectorized r…
Capstan: A Vector RDA for Sparsity
Alexander Rucker, Matthew Vilim, Tian Zhao +3
This paper proposes Capstan: a scalable, parallel-patterns-based, reconfigurable dataflow accelerator (RDA) for sparse and dense tensor applications. Instead of designing for one a…
Efficient Multiway Hash Join on Reconfigurable Hardware
Kunle Olukotun, Raghu Prabhakar, Rekha Singhal +2
We propose the algorithms for performing multiway joins using a new type of coarse grain reconfigurable hardware accelerator~-- ``Plasticine''~-- that, compared with other accelera…
Generating Configurable Hardware from Parallel Patterns
Raghu Prabhakar, David Koeplinger, Kevin Brown +4
In recent years the computing landscape has seen an in- creasing shift towards specialized accelerators. Field pro- grammable gate arrays (FPGAs) are particularly promising as they…