5 citations · 9 across the 9 of their papers we have counts for
5 papers · 1 filter
RLIBM-PROG: Progressive Polynomial Approximations for Fast Correctly Rounded Math Libraries
Mridul Aanjaneya, Jay P. Lim, Santosh Nagarakatte
This paper presents a novel method for generating a single polynomial approximation that produces correctly rounded results for all inputs of an elementary function for multiple re…
RLIBM-ALL: A Novel Polynomial Approximation Method to Produce Correctly Rounded Results for Multiple Representations and Rounding Modes
Jay P. Lim, Santosh Nagarakatte
Mainstream math libraries for floating point (FP) do not produce correctly rounded results for all inputs. In contrast, CR-LIBM and RLIBM provide correctly rounded implementations…
SPOTS: An Accelerator for Sparse Convolutional Networks Leveraging Systolic General Matrix-Matrix Multiplication
Mohammadreza Soltaniyeh, Richard P. Martin, Santosh Nagarakatte
This paper proposes a new hardware accelerator for sparse convolutional neural networks (CNNs) by building a hardware unit to perform the Image to Column (IM2COL) transformation of…
Sound, Precise, and Fast Abstract Interpretation with Tristate Numbers
Harishankar Vishwanathan, Matan Shachnai, Srinivas Narayana +1
Extended Berkeley Packet Filter (BPF) is a language and run-time system that allows non-superusers to extend the Linux and Windows operating systems by downloading user code into t…
RLIBM-32: High Performance Correctly Rounded Math Libraries for 32-bit Floating Point Representations
Jay P. Lim, Santosh Nagarakatte
This paper proposes a set of techniques to develop correctly rounded math libraries for 32-bit float and posit types. It enhances our RLibm approach that frames the problem of gene…