Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators

We show that DNN accelerator micro-architectures and their program mappings represent specific choices of loop order and hardware parallelism for computing the seven nested loops of DNNs, which enables us to create a formal taxonomy of all existing dense DNN accelerators. Surprisingly, the loop transformations needed to create these hardware variants can be precisely and concisely represented by Halide's scheduling language. By modifying the Halide compiler to generate hardware, we create a system that can fairly compare these prior accelerators. As long as proper loop blocking schemes are used, and the hardware can support mapping replicated loops, many different hardware dataflows yield similar energy efficiency with good performance. This is because the loop blocking can ensure that most data references stay on-chip with good locality and the processing units have high resource utilization. How resources are allocated, especially in the memory system, has a large impact on energy and performance. By optimizing hardware resource allocation while keeping throughput constant, we achieve up to 4.2X energy improvement for Convolutional Neural Networks (CNNs), 1.6X and 1.8X improvement for Long Short-Term Memories (LSTMs) and multi-layer perceptrons (MLPs), respectively.Comment: Published as a conference paper at ASPLOS 202

Simulation of char-pellet combustion and sodium release inside porous char using lattice Boltzmann method

Char-pellet combustion is studied with the lattice Boltzmann method (LBM) including sodium release and the ash inhibition effect on oxygen diffusion in the porous char. The sodium release and the shrinking of the char pellet are simulated by accounting for the reactions occurring both in the solid and gas phases. The combustion of a single char pellet is considered first, and the results are compared against measurements. The simulation of the pellet mass, pellet temperature and sodium release agreed well with in-house optical measurements. The validated lattice Boltzmann approach is then extended to investigate the combustion of porous char and sodium release inside the porous medium. The pore-structure evolution and the flow path variation are simulated as combustion proceeds. The simulations reproduce the expected different behaviors between the combustion products (CO and CO2) and the released volatile, here the sodium vapor. The combustion products are mostly generated at the flame front and then transported by the flow and molecular diffusion inside the complex porous char structure. However, the volatile sodium vapor forms in the entire porous char and tends to accumulate in regions where the flow motion stays weak, as in internal flow microchannels, or blocked, as in closed pores. These results confirm the potential of the LBM formalism to tackle char-pellet combustion accounting for the topology of the porous medium.National Natural Science Foundation of China; China Postdoctoral Science Foundation; Royal Society and the Engineering and Physical Sciences Research Council (EPSRC) (UK

Perturbed autophagy and DNA repair converge to promote neurodegeneration in amyotrophic lateral sclerosis and dementia

Maintaining genomic stability constitutes a major challenge facing cells. DNA breaks can arise from direct oxidative damage to the DNA backbone, the inappropriate activities of endogenous enzymes such as DNA topoisomerases, or due to transcriptionallyderived RNA/DNA hybrids (R-loops). The progressive accumulation of DNA breaks has been linked to several neurological disorders. Recently, however, several independent studies have implicated nuclear and mitochondrial genomic instability, perturbed co-transcriptional processing, and impaired cellular clearance pathways as causal and intertwined mechanisms underpinning neurodegeneration. Here, we discuss this emerging paradigm in the context of amyotrophic lateral sclerosis and frontotemporal dementia, and outline how this knowledge paves the way to novel therapeutic interventions

Determination of Picogram Levels of Diacerein in a Pharmaceutical Formulation by Flow-Injection Chemiluminescence

A simple, sensitive and inexpensive method for determination of diacerein by flow-injection chemiluminescence was proposed, based on the quenching effect of diacerein on the luminol-protein (bovine serum albumin, BSA) reaction. It was found that the decrement of CL intensity was linearly proportional to the logarithm of diacerein concentration ranging from 5.0 to 7.0×103 pg·mL-1 (r = 0.9968), with the limit of detection (LOD) of 1.0 pg·mL-1 (3σ). The proposed procedure was successfully applied to the determination of diacerein in pharmaceutical formulation, human saliva, and serum samples without interference from its potential impurities, with the recoveries ranging from 96.4% to 104.0% and the relative standard deviations (RSDs) less than 4.0% (n=6)

Determination of Picogram Levels of Diacerein in a Pharmaceutical Formulation by Flow-Injection Chemiluminescence

A simple, sensitive and inexpensive method for determination of diacerein by flow-injection chemiluminescence was proposed, based on the quenching effect of diacerein on the luminol-protein (bovine serum albumin, BSA) reaction. It was found that the decrement of CL intensity was linearly proportional to the logarithm of diacerein concentration ranging from 5.0 to 7.0×103 pg·mL-1 (r = 0.9968), with the limit of detection (LOD) of 1.0 pg·mL-1 (3σ). The proposed procedure was successfully applied to the determination of diacerein in pharmaceutical formulation, human saliva, and serum samples without interference from its potential impurities, with the recoveries ranging from 96.4% to 104.0% and the relative standard deviations (RSDs) less than 4.0% (n=6)

State of Health Diagnosis and Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Multi-Feature Data and Mechanism Fusion

State of Health (SOH) Diagnosis and Remaining Useful Life (RUL) Prediction of lithium-ion batteries (LIBs) are subject to low accuracy due to the complicated aging mechanism of LIBs. This paper investigates a SOH diagnosis and RUL prediction method to improve prediction accuracy by combining multi-feature data with mechanism fusion. With the approach of the normal particle swarm optimization, a support vector regression (SVR)-based SOH diagnosis model is developed. Compared with existing works, more comprehensive features are utilized as the feature variables, including three aspects: the representative feature during a constant-voltage protocol; the capacity; internal resistance. Further, the optimized regularized particle filter (ORPF) model with uncertainty expression is integrated to obtain more accurate RUL prediction and SOH diagnosis. Experiments validate the effectiveness of the proposed method. Results show that the proposed SOH diagnosis and RUL prediction method has higher accuracy and better stability compared with the traditional methods, which help to realize the decision of the maintenance process

Development of reduced and optimized reaction mechanism for potassium emissions during pulverized-biomass combustion based on genetic algorithms

International audienceA reduced mechanism for potassium chemistry under combustion conditions is derived from a detailed chemical mechanism for alkali metal emissions (Glarborg and Marshall, 2005), which could be useful for three-dimensional (3D) numerical simulations of potassium emissions by biomass combustion furnaces. An automated chemistry reduction and optimization approach relying on canonical micro-mixing problem is applied to develop the reduced mechanism, whose performance is then evaluated in two-dimensional (2D) carrier-phase direct numerical simulation (DNS) of pulverized-biomass combustion. Good agreements are achieved between predictions of the reduced and the detailed mechanisms on the four major potassium species, i.e., K, KOH, KCl and K 2 SO 4. The prediction capabilities of the reduced mechanism for various K/Cl/S ratios in the volatiles are further investigated by a parametric study with 14 two-dimensional DNS cases. The potassium chemistry under those various conditions are predicted well by the reduced potassium mechanism with a CPU cost reduction reaching up to 71.3% compared to the detailed reference mechanism

Reduced chemical reaction mechanisms for simulating sodium emissions by solid-fuel combustion

International audienceStarting from a reference and comprehensive chemical mechanism for alkali metal emissions (Glarborg and Marshall, 2005), combined with an hydrocarbon oxidation described with a skeleton mechanism (Kazakov and Frenklach, 1994), reduced and optimized chemical kinetics are derived. The objective is to provide a set of chemical schemes useful for three-dimensional (3D) numerical simulations of alkali metal emissions by pulverized solidfuel combustion systems. An automated procedure relying on one-dimensional (1D) premixed flames is applied to obtain a combined reduced mechanism, whose performance is then evaluated in one-dimensional strained diffusion flames, micro-mixing based canonical problems and three-dimensional carrier-phase direct numerical simulation (DNS) of coal combustion. Predictions of the reduced mechanism on major sodium species, i.e., Na, NaOH, NaCl and Na 2 SO 4 agree well with that of the detail reference scheme under all the considered conditions. A parametric study with 14 two-dimensional (2D) DNS cases is then performed to better understand the reactive flow properties and estimate the prediction capabilities of the reduced mechanism for various Na/Cl/S ratio in the volatiles. After pursuing the chemistry reduction, a global sodium mechanism with only 9 species and 8 reaction-steps is also discussed. The systematic comparison between the 3D DNS results obtained with the reference chemical scheme against those with the reduced ones confirm the validity of the reduction strategy. A reduction of up to 84% in computational cost is reached with the optimized global scheme, thus allowing for addressing real pulverized-coal combustion systems

Ultrasmall metal alloy nanozymes mimicking neutrophil enzymatic cascades for tumor catalytic therapy

Abstract Developing strategies that emulate the killing mechanism of neutrophils, which involves the enzymatic cascade of superoxide dismutase (SOD) and myeloperoxidase (MPO), shows potential as a viable approach for cancer therapy. Nonetheless, utilizing natural enzymes as therapeutics is hindered by various challenges. While nanozymes have emerged for cancer treatment, developing SOD-MPO cascade in one nanozyme remains a challenge. Here, we develop nanozymes possessing both SOD- and MPO-like activities through alloying Au and Pd, which exhibits the highest cascade activity when the ratio of Au and Pd is 1:3, attributing to the high d-band center and adsorption energy for superoxide anions, as determined through theoretical calculations. The Au1Pd3 alloy nanozymes exhibit excellent tumor therapeutic performance and safety in female tumor-bearing mice, with safety attributed to their tumor-specific killing ability and renal clearance ability caused by ultrasmall size. Together, this work develops ultrasmall AuPd alloy nanozymes that mimic neutrophil enzymatic cascades for catalytic treatment of tumors